2011
DOI: 10.1057/fsm.2011.28
|View full text |Cite
|
Sign up to set email alerts
|

Effects of demographic factors on bank customers’ attitudes and intention toward Internet banking adoption in a major developing African country

Abstract: This study provides an African perspective to the global research and literature on retail customer adoption of Internet banking (IB). It empirically examines the infl uence of seven demographic variables -age, gender, level of education, marital status, employment status, income level and area of residence -on retail banking customers ' behaviours toward IB adoption in a major developing African country -Nigeria. A sample of 500 customers was surveyed, and ANOVA and multiple regression analyses were used in t… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1
1
1
1

Citation Types

3
24
1
4

Year Published

2014
2014
2025
2025

Publication Types

Select...
8
1

Relationship

1
8

Authors

Journals

citations
Cited by 35 publications
(32 citation statements)
references
References 49 publications
3
24
1
4
Order By: Relevance
“…Aside from the studies which focused on the effects of innovation characteristics, others have explored the potential impact of some individual variables in explaining innovation adoption. These include surface personal factors such as demographics (gender, age, income levels) (Onyia and Tagg, 2011;Laukkanen and Pasanen, 2008;Nilsson, 2007;Laforet and Li, 2005;Mattila, 2003).Overall, the results from these studies indicate that the early adopters of M-banking were relatively young (between the ages of 25 and 34), average income earners, and white-collar urban workers. These findings, are by no means, conclusive given the dynamic and accelerated change in consumer access to mobile phones and other forms internet technologies during the last decade (Quinn et al, 2016;Thakur and Srivastava, 2014;Al-Jabri and Sohail, 2012 ).…”
Section: Effect Of Personal Factorsmentioning
confidence: 92%
“…Aside from the studies which focused on the effects of innovation characteristics, others have explored the potential impact of some individual variables in explaining innovation adoption. These include surface personal factors such as demographics (gender, age, income levels) (Onyia and Tagg, 2011;Laukkanen and Pasanen, 2008;Nilsson, 2007;Laforet and Li, 2005;Mattila, 2003).Overall, the results from these studies indicate that the early adopters of M-banking were relatively young (between the ages of 25 and 34), average income earners, and white-collar urban workers. These findings, are by no means, conclusive given the dynamic and accelerated change in consumer access to mobile phones and other forms internet technologies during the last decade (Quinn et al, 2016;Thakur and Srivastava, 2014;Al-Jabri and Sohail, 2012 ).…”
Section: Effect Of Personal Factorsmentioning
confidence: 92%
“…The items measured each of the five (5) SERVQUAL dimensions on a 7-point Likert-style scale ranging from 'strongly disagree' (1) to 'strongly agree' (7) The main data collection was from customers of 14 major health insurance companies across the UAE. Due to time and cost constraints, the convenient intercept (White and Nteli, 2004;Onyia and Tagg, 2011) and the snowball (Cueller et al, 2005) sampling methods were applied in recruiting the respondents. Twenty five (25) postgraduate students of the Australian University of Wollongong in Dubai were recruited and trained to administer the paper-based questionnaires in the 7 regions of the UAE, in line with Pikkarainen et al (2004) and Waite and Harrison (2004).…”
Section: Methodology and Data Collectionmentioning
confidence: 99%
“…For example, research has shown that equal number of male and female customers now use IB in the UK (Ilett, 2005). This trend is also gradually becoming noticeable in many developing countries where the population of women engaged in activities previously considered the exclusive preserve of men has been growing steadily over the years, including IB-adoption (Onyia and Tagg, 2011).…”
Section: Conceptual Background Customer Demographics and Ib Adoptionmentioning
confidence: 98%
“…This motivates others to try using the IB-option as well (see King and Gribbins, 2002;Howcroft et al, 2002;Sohail and Shanmugham, 2003;Laforet and Li, 2005;Rotchanakitumnuai and Speece, 2005;Lichtenstein and Williamson, 2006;Poon, 2008). On the contrary, the costs of computer ownership, internet connection, and "special service" fees charged by financial institutions for IB-usage in developing countries often constrain IB-adoption in those countries (see Shih and Fang, 2004;Chiemeke et al, 2006;Boateng and Molla, 2006;Onyia and Tagg, 2011). Based on the foregoing, we have extracted the eight most significantly validated indicator-variables in our results and harnessed them into a final model of potential universal antecedents of IB-adoption, especially given that they have also been validated in various studies from several other countries.…”
mentioning
confidence: 99%