The Moderating Effect of Individual Differences on the Acceptance and Use of Internet Banking: A Developing Country Perspective

The Moderating Effect of Individual Differences on the Acceptance and Use of Internet Banking: A Developing Country Perspective

Mazen El-Masri
Copyright: © 2020 |Pages: 22
DOI: 10.4018/JECO.2020070106
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Abstract

This research examines factors influencing the acceptance of internet banking (IB) in Lebanon. It extends the unified theory of acceptance and use of technology (UTAUT) model by including trust as a proxy and then investigates the moderating effect of a set of socio-demographic variables (gender, age, experience) in shaping consumer perceptions towards using IB. A cross-sectional survey was used to collect data from 408 IB consumers in Lebanon. Structural equation modelling was employed as the main method of analysis. The results show that behavioral intention (BI) was significantly influenced by performance expectancy (PE), social influence (SI), trust (TRU) and effort expectancy (EE) in their order of influencing power. Moreover, facilitating conditions (FC) and BI significantly influenced use behavior (UB). Gender moderated the relationship between PE_BI and SI_BI, age moderated the relationship between PE_BI, EE_BI, and FC_UB, and experience moderated the relationship between EE_BI and SI_BI. The theoretical and practical implications are discussed at the end of the article.
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Introduction

The rapid growth of the Internet and information and communication technologies (ICT) had significant impacts on the methods banks use over the last decade to deliver financial services to their consumers (Shareef et al., 2017). Banks worldwide provided electronic services online—termed internet banking (IB)—that helped them operate, deliver financial services, and compete with other banks while reducing operations cost, creating new distribution channels, retaining existing customers, improving customer satisfaction and increasing effective market coverage (Ruangkanjanases and Wongprasopchai, 2017). Internet banking refers to “systems that enable bank customers to get access to their accounts and general information on bank products and services through the use of bank ̳s website, without the intervention or inconvenience of sending letters, faxes, original signatures and telephone confirmations” (Dube et al., 2009; Thulani et al., 2009).

Despite these advantages, large groups of consumers have shown reluctance to use IB services (Lee, 2009; Bons et al., 2012; Haking et al., 2017; Alalwan et al., 2016; Oruç and Tatar, 2017). Consumers may have serious concerns about using Internet technology for banking. Much of these concerns may illuminate the customer’s perceptions of the degree of ease of using IB, the needed skills, security of IB, IB’s usefulness, and the knowledge about IB services (Yousafzai, 2012).

Indeed, IB success not only rely on the support of banks or governments’ investments, but also on customers’ willingness to adopt the technology (Khan et al., 2017). As with any other technology, the so-called “digital divide” will play an important role in adopting IB services. These differences were attributed to biology, socialization, and information processing style (Venkatesh et al., 2012). For instance, Sarabdeen and Rodrigues (2010) observed that “the involvement of women as consumers, especially of computer-based technologies has been much slower” (p. 125). Indeed, the rate adoption of IB services has been observed to differ according to people’s age, gender, and experience (Martins et al., 2014; Alalwan et al., 2016). Additionally, “customer characteristics are important given the high involvement of customers in the online service context” (Yousafzai and Yani-de-Soriano, 2012, p. 61). More specifically, demographic characteristics (age, gender, experience) have been found to influence customers’ behavioral intentions toward using certain technologies (Yousafzai and Yani-de-Soriano, 2012; Mzoughi and M’Sallem, 2013; Dwivedi et al., 2015). Yet, research examining the impact of individual differences on consumers’ behavior has been sparse (see Venkatesh and Zhang, 2010; Richard et al., 2010).

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