Purpose – The purpose of this paper is to examine if high branch fees, branch dissatisfaction as well as any previous experience of Greek banking customers with other banking technologies (i.e. Automated Teller Machines (ATMs)) have any impact on the probability of internet banking adoption. Further, the authors comment on the socio-economic and demographic characteristics of Greek banking customers, which effect the decision to adopt internet banking services. Design/methodology/approach – The authors employed the logistic regression model to examine the probability of Greek customers adopting internet banking based on certain demographic characteristics but also due to high branch fees, any dissatisfaction with branch services or due to previous experience of electronic banking technologies (ATMs). Findings – After estimating a logistic model, the authors report that branch dissatisfaction and high branch fees have no impact to the internet banking adoption in Greece, therefore Greek customers prefer to visit branches and are willing to pay high fees for the transactions. However, the authors find that ATM users are more likely to adopt internet banking services in Greece. Research limitations/implications – The authors should employ a technology acceptance model, to test the effect of perceived ease-of-use, perceived usefulness and technology self-efficacy of customers on the probability of e-banking adoption. The authors should also examine other hypotheses using recent data from other European countries and compare the results with those from Greece. Practical implications – The findings are strongly recommended to Greek bank managers. Originality/value – The research is primarily motivated by the lack of similar studies to explain empirically the characteristics of Greek bank customers which affect the adoption of internet banking.

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This paper investigates the effect of Automated Teller Machines (ATMs), Information Technology (IT) investments and other determinants on the efficiency and profitability of Greek commercial banks. Following the two-step procedure, (i) efficiency is derived via the non-parametric Data Envelopment Analysis (DEA) technique under the Variable Returns to Scale (VRS) assumption, and (ii) efficiency scores are linked to a series of determinants of bank efficiency using a Tobit regression model. We find that profitability (ROAA and ROAE), ATMs and capitalisation show a negative impact on the efficiency of Greek banks. We also report that banks' size, capitalisation, IT investments and ATMs do not have any effect on the ROAA or the ROAE but they have a positive effect on the fees and commissions. However, we find that ATMs have a negative effect on the net interest income.