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C E S P R I

Centro di Ricerca sui Processi di Innovazione e Internazionalizzazione

Universit Commerciale "Luigi Bocconi"

via R. Sarfatti 25 - 20136 Milano

tel. 02 5836.3395/7 - fax 02 5836.3399

http://www.cespri.uni-bocconi.it/

Nicoletta Corrocher

Does Internet banking substitute traditional banking?

Empirical evidence from Italy

WP n. 134 Novembre 2002

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ABSTRACT

The paper aims at examining the drivers of the adoption of the Internet banking, in order to

understand its role with respect to the traditional banking activity and to offer a comprehensive

picture of the diffusion of such a technology within the sector. In doing so, it analyses the role of

firm-specific and non firm-specific (technology, market, environment) characteristics in influencing

the decision to adopt the new technological platforms to perform on-line banking transactions

within the retail segment of the financial sector in Italy. The main purpose of this paper is to

investigate the relationship between the Internet banking and the traditional banking activity, in

order to understand if these two systems of financial services delivery are perceived as substitutes

or complements by the banks.

JEL Classification: O3; L0; L86

Keywords: Technology Diffusion; Internet; Banking Sector

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1.IntroductionThe paper aims at examining the drivers of the adoption of the Internet banking, in order to

understand its role with respect to the traditional banking activity and to offer a comprehensivepicture of the diffusion of such a technology within the sector. In doing so, it analyses the role of

firm-specific and non firm-specific (technology, market, environment) characteristics in influencing

the decision to adopt the new technological platforms to perform on-line banking transactions

within the retail segment of the financial sector in Italy. The main purpose of this paper is to

investigate the relationship between the Internet banking and the traditional banking activity, in

order to understand if these two systems of financial services delivery are perceived as substitutes

or complements by the banks. The interest towards this issue has been stimulated simultaneously by

the recognition of the revolutionary characterisation of the Internet within the existing technological

trajectory of ICT and by the growing importance of the service industries - especially information-

intensive sectors - in the process of development of innovations.

Adoption-based models of diffusion of innovation have a long history both of theoretical

developments and of empirical studies (for a review see Karshenas and Stoneman, 1995; Baptista,

1999). Applications to the banking sector, however, are only a few ones and most of them deal with

the diffusion of ATMs in the financial sector (Hannan and McDowell, 1984; Escuer et al., 1991;

Pennings and Harianto, 1992; Ingham and Thompson, 1993; Hester et al., 2000), and only a few

authors have concentrated on more recent innovations (Buzzacchi et al., 1995; Daniel, 1999; Mahler

and Rogers, 1999). Very few studies have so far been published on the diffusion of Internet-based

technological platforms for banking and just two of them have dealt with the diffusion of any

technological innovations in the Italian banking system, which is the third banking system in the

European Union by market capitalisation (after UK, France and Sweden).

The paper is structured as follows. First, some general remarks on Internet banking as an innovation

and on the relationship between this new technological platform and the existing banking activity

are presented. Second, an overview of the most important contributions on the adoption of new

technologies in the banking sector is provided. The aim of this section is to identify the main factors

that have been taken into account in order to explain the diffusion of innovations in this industry. In

the third part, a description of the available data sets concerning the characteristics of Italian banks

and the pattern of adoption of the new technology is offered. In this context, an empirical model for

the examination of the adoption of the Internet banking technology is developed, on the basis of the

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available data. Finally, the results of the empirical analysis are illustrated and interpreted and

conclusions are drawn on the relationship between Internet banking and the traditional banking

system.

2.Internet banking as a radical innovationInternet banking identifies a particular set of technological solutions for the development and the

distribution of financial services, which rely upon the open architecture of the Internet. The users

can conduct financial transactions anywhere - at home, at the office or at school - as long as they

have a computer and a modem. With the implementation of an Internet banking system, the banks

maintain a direct relationship with the end users via the web and are able to provide a personal

characterisation to the interface, by offering additional customised services (Cronin, 1998). A

common view of Internet banking is that it represents a process innovation, because the

technological developments behind this innovation seem to improve exclusively the operational

procedures. Following this perception, in OECD (2000), it is stated that the new ICT affect the

relationship between producers and consumers, in that the personal contact becomes less essential,

because in many cases the services can be provided much more efficiently via the Internet or

through other communications modes. This is a somewhat misleading perception concerning the

impact of Internet-based technologies on the provision of services and in particular on the

distribution of information-intensive services such as the financial ones, whose content can be

easily transformed into an electronic format and delivered over the web.

However, the concept of an evolutionary process within the banks output from products to

services1 and the characteristics of the Internet lead us to adopt a different view of the Internet

banking. This technological innovation represents a process innovation, since it strengthens the

interaction between the bank and its customers and enhances the distribution function. However, it

can be conceived also as a product innovation, since it embodies the creation of new products as

such and the development of innovative combinations of the existing products. This second aspect

1 At a very general level, it is possible to state that the output of the back office operations are the financial products thatare successively made part of the distribution process and delivered to the end users through the front office operations.In this second phase, additional value and functionality are given to the financial products, so that they assume the

identity of financial services. In particular, the value added stems from the interactivity with the final users and theconsequent customisation of the product, so that what is actually distributed on the market is a financial service. Thereis therefore a process of evolution of the output of the banking firm from the simple form of financial product to the

more sophisticated form of financial service and it could be argued that the more value is added to the end users via theintermediation of the bank, the more the output of financial institutions can be considered a service. A high level of

customisation and a direct relationship between the bank and its users is what differentiates a standardised financialproduct from a financial service, which appears to be more customised and personalised.

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is made possible by the potentialities of the Internet, which encourages and facilitates a move from

hierarchical single-supplier relationships, to market-based multiple-suppliers scenarios (Daniel,

1999). Bracchi et al. (2000) stress that Internet banking allows customers to interact more with the

front office operations and, at the same time, it allows the bank to concentrate the back office

operations by increasing their efficiency. According to such perspective, Internet banking

constitutes an innovation both in the processes of production and in the distribution of financial

services.

On the customer side, the Internet gives more information on the types of financial services of

different banks and allows comparisons between the available offerings. On the bank side, the new

technologies offer greater information on the users needs and requirements and therefore they

permit to develop customised services. Moreover, the Internet represents a valuable instrument to

monitor the activity of the competitors. This may drive networking and interaction between the

different banks, but may also strengthen the competition and make the selection process severe. The

Internet banking constitutes a complex innovation that does not fall into the simple categorisation of

product/process innovations, but encompasses both, as a part of a continuum. In other words, in the

case of Internet banking, as in the case of other ICT-based innovations, it is not possible to talk

about a temporal sequence of product and process innovations. The pervasiveness of such

technological developments in the sector allows for the simultaneous presence and, even more, for

the strong interdependence of the two types of innovations.

In this respect, the notion of service innovations becomes quite helpful in identifying the

characteristics of the Internet banking. It is possible to conceptualise innovation in services as a

complex entity, in which elements of product and process innovation closely interact with each

other. It is reasonable to argue that Internet banking entails all the peculiarities of service

innovation, which combines some forms of product innovation and some forms of process

innovation. It is particularly the interactivity and the information intensity of the new service that

matters for the characterisation of the Internet banking and for the fact that both process and product

innovations emerge in such a context.

The discussion on the nature of the Internet banking as a service innovation receives some more

insights if one considers the relationship between the traditional banking activity and the Internet

banking. On the one hand, it is possible to perceive Internet banking (and in general electronic

banking) and the traditional banking as two substitute forms of managing financial transactions. An

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alternative perspective is to consider these two systems as complementary solutions for the

provision of financial services. The first approach naturally leads to view the Internet banking as a

second-best system compared to the traditional banking: the personal contacts between the banks

and the final users are eliminated and the non-verbal dimension of the communication cannot be

perfectly reproduced over the Web. However, it is worth considering that there is not a substitution

between the technological systems and the human resources involved in the banking activity, and

that the implementation of new Internet-based solutions require both the development of new

knowledge and competencies, in order to increase the functionality and the value of the financial

services for the end users, and the reinforcement of the existing routines and skills, in order to adapt

them to the new paradigm. Therefore it is more appropriate to adopt a perspective that emphasises

the complementarity between the traditional banking activity and the new Internet banking solutions

and considers them two separate, but not incompatible systems of providing financial services.

The pattern of evolution of the banking activity does not prevent us to regard the different forms as

sequential, but not mutually excluding technological and business models for the provision of

financial services. In the initial phase of the development of electronic banking, the new system was

conceived as a substitute for the existing model and the tendency of the banks was to replicate the

traditional banking activity, by adding new features and functionality made available by the

emergence of the new technologies. However, it soon became clear that the two forms of banking

were not incompatible and could coexist within the same environment. Furthermore, banks realised

that the potential of each these models would have been strengthened, if both systems had been put

in place. This means that the capability of the new technological systems could not be exploited

exclusively by applying the new ICT to the existing systems, but required the creation of different

technological and business models2. It is true that the Internet banking cannot provide customers

with the same range of financial services of the traditional bank, especially as far as the type and

degree of interaction is concerned. However, it is also true that it allows the emergence of new

typologies of services and the possibility of making use of them on a continuous basis. It is not

possible to establish a once-for-all best solution for the implementation of the banking activity, but

it is reasonable to argue that the combination of connectivity, continuity of the service, user

2

In this respect, Filotto (2000) makes an interesting comparison between the transition from the traditional banking tothe Internet banking and the evolution of the flight systems. For ages, the human beings tried to replicate the flight ofthe birds and built a variety of flying machines based upon a mechanism of flexible wings that never worked properly.

The history of the flight with heavy machines started with the introduction of fixed wings, which allowed a much highercarrying capacity compared to the flexible wings, suitable to carry only very light weights. This example shows how the

best results are often achieved not by reproducing the existing models with the new technologies, but by identifyingnew trajectories that can fully exploit the potential of such new technologies.

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interface and low costs makes the electronic bank a model that complements and strengthens the

functionality of the existing one.

The above considerations have a significant impact on the identification of the determinants of

Internet banking adoption by banks. It is often argued that a process innovation offers lower costs

and provides benefits more to the existing customers of a firm, while a product innovation is

directed to capture new users and to enlarge the market share. The analysis allows us to investigate

the relationship between the Internet banking and the traditional banking in terms of

substitution/complementarity and to understand which bank-specific characteristics are most

conducive to the adoption of Internet banking.

3.Empirical contributions on the adoption of innovations in the banking sectorIt is quite significant that the appearance of the initial contributions on this topic followed the

introduction of the ATMs in the banking industry, which was perceived as an important example of

ICT-based service innovation and therefore attracted the interest of many researchers. As a

consequence of this, a process of data collection started in the industry, which allowed the

development of empirical analysis on the pattern of adoption of this innovation by banks, although

the literature has also investigated the adoption of other types of new technologies. In the

examination of the main features of the different studies, we will pay particular attention to the

determinants of adoption of the new technologies identified by the relevant contributions. This is

because such an analysis constitutes a useful starting point for the development of the empirical

model regarding the adoption of Internet banking in Italy, particularly as far as the choice of

explanatory variables is concerned.

Hannan and McDowell (1984) investigate the determinants of adoption of ATMs in the US

financial sector. The results of the analysis largely confirm the assumptions made by the authors.

Market concentration and firms size both have a significant and positive impact on the probability

of adoption of ATMs. Concentration allows a faster introduction of new technologies and produces

dynamic efficiency benefits (despite lowering static efficiency gains). With reference to firm size,

on the other hand, large firms have a more positive attitude towards the introduction of new

technologies than small firms benefit from relevant economies of scale in the use of ATMs. As far

as other market characteristics are concerned, market growth does not have a significant impact on

the adoption, while the wage rate shows positive and significant coefficients. This means that

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reducing the operating costs represents one of the most important drivers of the adoption of ATMs.

A very interesting result concerns the role of firm profitability: the impact of profits on the

conditional probability of adoption is negative but statistically insignificant, and this means that

there is no evidence of the role of financial constraints in the technological strategies of banks. On

the contrary, the specific product mix of a bank greatly affects to a great extent the adoption of

ATMs: the positive coefficient of this variable is consistent with the idea that, since cash

withdrawals from demand deposits are the most common type of transactions performed with the

ATMs, a high proportion of demand deposits over total deposits acts as a driver of the adoption.

As far as the dummy variables are concerned, the findings show a positive and significant effect of

the existence of branching restrictions on the probability of adoption, suggesting that banks are

more likely to adopt ATMs when alternative methods of providing value-added services to

customers are limited. This is further supported by the fact that banks seem to be more likely to

introduce the new technological systems, if the regulations allow the setting up of off-premise

ATMs. Other important results relate to the fact that banks that are owned by a holding company

are more likely to adopt the innovation, as well as banks that operate in an urban environment -

although the coefficient for this variable is marginally significant.

Along this line of research, Ingham and Thompson (1993) aim at investigate the determinants of the

adoption of ATMs in the UK financial sector. The results of this analysis are largely consistent with

the findings of Hannan and McDowell (1984). Firm size has the expected positive effect on the

adoption of new technologies, as well as labour costs. The most interesting result relates to the

effect of branching, which is negative, although marginally significant: according to the authors,

this means that the sunk costs of building a structure of branches have an important role in

determining the probability of adopting the ATMs, as compared to the alternative effect of cost

reduction deriving from the introduction of the new technology. However, we believe that the

negative relationship between branching intensity and the probability of adoption could also be

determined by the fact that banks with a high number of branches have a very close contact with the

customers and do not feel the need for implementing other systems for financial services delivery.

The proportion of non-retail deposits shows a negative but not significant effect, as well as the

variable identifying the strategy of the building societies (more or less close to the one of

commercial banks). Finally, advertising seems to affect positively the adoption of ATMs and this

again accounts for a relevant scale effect.

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Another interesting contribution in this context is the one by Escuer et al. (1991) on the

determinants of adoption of the teleprocess terminals by Spanish commercial and savings banks.

The main object of investigation is the diffusion of a new process technology developed in an

outside industry within a population of homogeneous firms operating in different geographical

markets. The theoretical model used to guide the empirical analysis is the probit model of adoption

of process innovations by business firms (Davies, 1979). The results show that adoption time is

minimised for a medium level of size, which identifies banks with deposits of approximately

400.000 million pesetas. Capital intensity is positively associated with the time of adoption, which

indicates that labour intensive banks adopt the new labour saving technology earlier than capital

intensive ones. Finally, the time of adoption is negatively related to the profitability, but the level of

statistical significance of this variable is quite low, which is a common result in the literature. The

authors apply the model also to savings banks, but extend it in order to account for the impact of the

market structure on the adoption of new technologies. In particular, they introduce two additional

determinants - market concentration and market growth - to explain adoption time. The empirical

analysis demonstrates that both these variables are significantly related to the decision to invest in

the innovation. In particular, the results indicate that the diffusion of the new technologies is faster

with intermediate levels of concentration in the market, i.e. with intermediate level of competition.

An interesting paper is the one by Pennings and Harianto (1992) that deals with the adoption of

video banking services within a sample of 152 of the largest 300 commercial banks in the US

between 1980 and 1987. The authors argue that the likelihood that banks invest in this technology is

positively associated with the accumulation of experience in the ICT area, with the capital

investments in systems and equipment, with the development of inter-firm linkages with firms in

the ICT, stock brokerage and insurance sectors and with other transactional providers. The study

takes into account four groups of determinants, related to technological experience, networking,

firm attributes and industry characteristics. The results of the model partially confirm the three

hypotheses made by the authors with reference to the determinants of adoption of video banking

services. Cumulative experience in technology and in inter-firm linkages are highly correlated,

meaning that they compete in explaining the probability of introducing the new technological

systems. Both these factors are conducive to innovation, although when they are introduced

together in the model, the most significant one is the existence of inter-firm linkages. Within this

category, it seems that the agreements involving inter-firm conduct stimulate technological

innovations, while inter-organisational relationships contribute to the diffusion of innovations. This

is not very surprising, since many technological activities entail some form of networking and

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hence technologically active firms are prominent also in inter-organisational strategies. However, it

is worth underlining that the exclusion of either variable from the model makes the other highly

significant. On the contrary, the productivity index and the investments in systems and equipment

have no significant effects. As far as firm and market attributes are concerned, firm size is the only

characteristic that has a significant impact on the adoption of video banking services.

Buzzacchi et al. (1995) develop a theoretical model to analyse the determinants of ICT-based

innovations in the banking sector and test it for the use of electronic payment systems of a sample

of 77 Italian commercial banks. The authors analyse four groups of factors that can drive the

diffusion of such services and refer to the structure and conduct of banks, the characteristics of their

market, and the driving forces of the technology. The empirical findings show that the level of IT

literacy accumulated during the mass automation regime is very important in explaining the

adoption of electronic banking services. On the contrary, the coefficients of technology-push

variables are not significant, meaning that technological leadership in the automation of back-office

operations does not provide banks with additional advantages. The demand-pull variables appear to

play a crucial role in affecting the innovation in the baking industry: however, this holds just for

banks that have a high level of IT-related skills, while technological laggards have reduced

capabilities to take advantage of favourable demand conditions. Market structure fails to prove any

effect on the introduction of innovations in electronic banking, while size exerts a positive but

decreasing effect. Furthermore, a banks market share does not evidence any effect upon the

adoption of innovations and the same holds for the profitability of a bank, meaning that banks do

not face liquidity constraints in the development of innovations.

Another study (Daniel, 1999) examines the provision of electronic banking in the UK and in the

Republic of Ireland and is based upon data from a questionnaire. The aim of the research is to

investigate the importance of a series of factors for the provision of electronic banking services: the

organisational culture of innovation, the market share or strength of the organisation, organisational

restrictions and limitations, the prediction of customer acceptance and the vision of the future. Most

respondents agree that providing electronic banking is crucial to meet the expectations of the

existing customers in terms of the range of products and services offered, and to capture new users.

With reference to the organisational limitations, the empirical findings suggest that financial

constraints and the scarce availability of human resources are the most important problems related

to the possible implementation of electronic banking. However, beyond these restrictions there are

also some cultural barriers, such as the lack of senior management support and commitment.

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Turning to the market variables, it is interesting to observe that most respondents forecast a low

usage of electronic banking by their customers, despite recognising that the uncertainty of customer

acceptance does not affect the adoption of these technologies and that the main reason for providing

such services can be identified in their value-added for the customers. Finally, the respondents

believe that the provision of electronic banking is fundamental for the future strategy of the bank,

since it reduces costs and offers a strong competitive advantage. In general, the vision of the future

is considered to be the most important factor stimulating the adoption of electronic banking

services, followed by customer acceptance, while organisational restrictions and limitations are

perceived as the least important variables that explain the provision of electronic banking: this

means that market drivers play a more significant role than organisational drivers.

Finally, Mahler and Rogers (1999) focus on the role of the critical mass in explaining the diffusion

of interactive communication innovations (of which Internet banking could be thought as the most

complex one). The starting point is the recognition that the adoption of this type of innovations

depends on the perceived number of other competitors that have already adopted them: therefore the

diffusion path does not follow the common S-shaped curve until a critical mass of users is reached.

The object of the analysis is the diffusion of twelve communication services in the German banking

industry, a sector which is a pioneer in the adoption of new telecommunications technologies. After

having collected the information from banks with respect to the relevance of these determinants for

not adopting the innovations, the authors conduct a factor analysis and extract three factors. The

first one is related to the poor service from the supplier and is explained by variables such as bad

service, resistance from employees, long waiting period, bad information from the supplier, bad

price/value ratio. The second factor identifies an ensemble of socio-technical determinants and

includes variables such as bad data security, lack of sufficient standards and organisational

problems. The third factor contains just one variable, i.e. the low rate of diffusion of the

innovations. The study then examines the relationship between these three obstacles to adoption and

the degree of innovativeness of German banks - that are divided into innovators, early adopters,

early majority, late majority and laggards (following Rogers, 1995). The low rate of diffusion is the

most important obstacle to the adoption for all the categories but for the innovators, that consider

the socio-technical reasons as being more important. Furthermore, for all the categories except for

the innovators, the poor service from the supplier is considered as more relevant than the socio-

technical reasons. The analysis shows that, whether or not the diffusion process of a specific

innovation has reached a critical mass, the obstacle to adoption represented by the low rate of

diffusion is of significant relevance for all the innovations, regardless of the presence of network

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externalities. Furthermore, these results are quite interesting because they put emphasis one the role

of suppliers in affecting the decisions of the banks to adopt the innovative services.

4.A model for the analysis of the adoption of Internet banking in Italy

The starting point for the analysis is the development of a model of duration to examine the

conditional probability of adoption of Internet banking. We provide the theoretical background

related to the specification of the model, explaining the approach used in the present research to

estimate the model. The second part concerns the description of the variables chosen as explanatory

factors of the adoption of Internet banking technology.

The object of investigation is the probability that a bank adopts in time t, given that it has not yet

adopted by that time: this conditional probability constitutes the dependent variable in the model. In

order to analyse the effect of covariates on the hazard rate, one of the most common model is given

by Coxs approach to the proportional hazard (Kiefer, 1988; Greene, 1997). The present study takes

this technique as the point of reference for the estimation of the model. This method is a

semiparametric approach to survival analysis. It does not require the probability distribution F(t) to

be specified and utilises regression parameters in the same way as generalised linear models. The

model specifies that

)'exp()()( 0 iii xthth =

so that the hazard functions of any two individuals are assumed to be constant multiples of each

other, the multiple being ))('exp( ji xx , the hazard ratio orincidence ratio. The function h0 is

the baseline hazard and represents the individual heterogeneity, while the set of parameters ho(t) can

be considered as nuisance parameters that merely control the parameters of interest for any

change in the hazard over time. In principle these parameters should be estimated for each

observation: however the Coxs partial likelihood estimator provides a method of estimating

without requiring the estimation ofho(t). Having described the theoretical framework, the next step

of the analysis will consist in the choice of the covariates Xthat explain the conditional probability

of failure (adoption).

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4.1The explanatory variablesThe first variable we take into account is the size of the potential adopters (banks), in line with the

existing studies related to the adoption of new technologies in the financial sector and in general tothe diffusion of innovations among firms (Karshenas and Stoneman, 1995). The most common

proxy for firm size is the number of employees; nonetheless, when analysing the financial sector,

the literature measures firm size with total assets3. In our investigation, we propose two different

specifications of the model, which alternatively include, as a proxy of firm size, the total assets and

the number of branches. As we will see later on, the main reason behind the use of two alternative

measures of firm size relies in the relation between these variables and other explanatory factors in

the model (e.g profits).

In general it is assumed that the size variable captures the scale effect, although some authors (Rose

and Joskow, 1990; Hannan and McDowell, 1994) argue that differences in firm size may also reveal

differences in managerial attitudes and in the risk aversion to experiment new technologies. In the

present study, we expect a positive relation between size and the conditional probability of

adoption, therefore believing that there exist significant economies of scale associated with the

implementation of Internet banking. This could be partly explained by the fact that a big bank

reduces its transaction costs much more than a small bank, if it offers its customers on-line banking

services, since it deals with a high number of customers and it manages a relevant amount of

financial operations. Beyond this, Internet banking platforms provide a way to facilitate the co-

ordination between the branches of a bank, which represents a strategic issue more for big

institutions than for small ones. However, some authors (Pennings and Harianto, 1992; Buzzacchi et

al., 1995) have underlined that in the smart automation regime, the importance of external sources

of technology should reduce the role of size as a determinant of adoption of innovations.

If we look at the pattern of adoption of Internet banking in Italy, we can see that the first adopters of

Internet banking technological systems were not the largest banks, but the medium size institutions.

Accordingly, although we believe in a positive relationship between size and the conditional

probability of adoption, we perform a non linearity test, introducing a term that represents size

squared (assets2 and branch2) to allow for more flexibility in the relationship and to investigate the

existence of a size most conducive to technological adoption. Based upon the results obtained in the

3

Other authors (e.g. Escuer et al., 1991, Buzzacchi et al., 1995) measure the size as the volume of bank deposits.

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descriptive statistics, we expect that the probability of adoption is positively affected by size up to a

certain point, but as banks become larger and larger, this relationship is inverted.

The second variable that is included in the range of independent variables is the profitability of the

bank, measured as total profits: the issue here is to test the importance of liquidity constraints in

funding the adoption of a new technology. The relationship between the profitability of a bank and

the conditional probability of adoption of a new technology does not appear to be significant in the

literature, and even when the profitability is measured with the return on equity - an indicator that

should help avoiding problems of correlations between profitability and size - the results do not

improve (Escuer et al., 1991; Pennings and Harianto, 1992; Buzzacchi et al., 1995). Despite this

evidence, we allow for the possibility of profits affecting the adoption and therefore do not make

any a-priori assumption on this relationship.

The third factor we consider is the share of interest margin over gross income, which illustrates the

characteristics of the activity of a bank. The introduction of a variable that identifies the product

mix of the bank is quite common in the literature on the diffusion of ATMs and usually the research

investigates the share of retail accounts over total deposits, because it is assumed that ATM services

are utilised mostly by retail accounts holders (see, for example, Ingham and Thompson, 1993). In

the present analysis, the variable into question indicates what is the magnitude of interest-based

transactions (e.g. loans) as compared to the total gross income. A bank with a high interest

margin/gross income ratio performs an activity that generates a high share of interest-based income

and could be considered less innovative than a bank with a high proportion of income deriving from

other value-added activities, such as brokerage.

This factor is quite relevant when taking into account the pattern of adoption of Internet banking.

On the one hand, banks need to find new ways of generating income other than interest-based

transactions, since these are less and less profitable due to the sharp decrease in the interest rates:

therefore going on-line could help the development of new value-added products and services and

this means that a high interest margin/gross income ratio could drive the adoption. On the other

hand, banks with a low interest margin/gross income ratio are already oriented towards more value-

added activities. It follows that the adoption of Internet banking, especially in a country like Italy

where the stock trading business has boomed dramatically in the last two or three years, would

prove to be particularly useful and efficient for such institutions. Furthermore, it is worth

remembering that non interest-based transactions involve a higher cost than interest-based ones: this

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means that the advantages of on-line banking stemming from the reduction of costs per transaction4

would be higher, the lower is the interest margin/gross income ratio. Despite the ambiguous effect

of the banking activity on the probability of adoption, we are more inclined to think that there exists

a negative relationship between the interest margin/gross income ratio and the adoption of Internet

banking.

It is quite common to assume that the adoption of innovations - particularly ICT-based innovations -

presents a high degree of persistence, so that a firm that has proven to be a heavy adopter in the

past, will continue to do so also in the future. In some cases of ICT-based innovations, there is also

an important effect of complementarity between different technologies, so that the adoption of a

specific innovation depends upon the previous adoption of a complementary technology (Pennings

and Harianto, 1992; Stoneman and Kwon, 1994; Buzzacchi et al., 1995; Colombo and Mosconi,

1995; Shapiro and Varian, 1999). The cumulative experience in information technology as a driver

of adoption of innovations is quite visible in the case of Internet banking, which involves both

telecommunications and computer technology and could not be adopted without the benefits of

commensurate learning curves. The capacity of banks to innovate around ICT depends very much

upon whether they have engaged in the acquisition of cumulated computer skills, developing an

absorptive capacity in the field.

Unfortunately the data we have on the banking sector in Italy do not allow us to identify a proper

measure of innovativeness, since we do not have data on IT systems expenditures or, more in

general, on R&D expenditures. Therefore, we measure the innovativeness of a bank as the

intensity of ATM adoption, i.e. as the share of ATMs over total branches. Since the first ATM

appeared a long time ago and most banks have an ATM in each branch (which means an intensity

of ATM adoption equal to 1), we generate a dummy variable. This dummy is equal to 0, if the ratio

between the number of ATM and the number of branches is1, and is equal to 1, if the ratio is

greater than 1 - meaning that the bank is actually more innovative than the average. Accepting this

indicator as a measure of the propensity to innovate, we expect a positive effect of this variable on

the probability of adoption.

4 The comparison between banking transaction costs by channel shows that Internet banking costs less than 1% of

traditional branch banking, with telephone banking being less than 50% as expensive as branch transactions and ATMtransactions costing 50% of telephone banking (Shroeder Salomon Smith Barney, 1999).

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The introduction of Internet-based technological systems is often seen as part of a strategy of cost

reduction, notwithstanding the need for substantial technological and marketing investments, for the

recruitment of new technological experts and for the creation of new job functions. As far as human

capital is concerned, the issue is quite straightforward, since the adoption of Internet banking tends

to reduce the cost of personnel, at least in the short term. If a bank sees the possibility of cost

reduction, it will be more inclined to adopt the new technology. In order to account for this variable,

we use a relative measure, i.e. the share of personnel expenditures over total assets.

As far as the costs of the infrastructure are concerned, the question is how the Internet banking is

perceived in relation to the existing banking structure. In line with Ingham and Thompson (1993),

we measure the intensity of branching as the adjusted number of branches over total assets. If banks

considered the sunk costs of having built up a branch network, this could retard the adoption of

Internet banking. Furthermore, banks with a significant number of branches are deeply rooted in the

geographical area where they operate: this means that they have well-established contacts with

customers and therefore do not feel the need to implement technological systems for the provision

of on-line financial services. According to this view, the Internet banking is considered as a

substitute for the branch activity: banks do not see many benefits stemming from the provision of

financial services over the Internet and may even perceive the existence of an opportunity cost to

switch to the on-line business. Alternatively, more intensively branched banks can see great

potentials for costs savings and the possibility of increasing the efficiency of their existing

operations, if Internet banking is perceived as a means of rationalising the existing network of

services distribution, without necessarily substituting it. Given this ambiguity, it is not possible to

make any a-priori assumption on the effect of branching intensity on the adoption.

Another variable included in the model is the age of a bank, that indicates how long the bank has

been operating. On the one hand, the age affects the structure and dynamics of the loss and profits

of the institution and the stability of the financial statements. A new bank usually faces losses due to

start up costs and this would lead to assume that older banks are more stable and can more easily

invest in Internet banking systems, relying upon their existing revenues. However, it is also true that

new banks are more flexible, do not have a legacy system to deal with, and face smaller managerial

obstacles to the adoption of the new technology. Furthermore, since the provision of on-line

banking services represents also a means to attract customers, it could constitute a strong incentive

for relatively new institutions. In view of these considerations, we do not make any a-priori

assumption on the effect of age on the adoption.

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The corporate governance of a bank is quite relevant in explaining the speed and intensity of

adoption of Internet banking5. The empirical evidence on Internet banking shows that most savings

banks have been fast adopters, while co-operative tend to be laggards. The model therefore includes

a dummy variable indicating the specific category of a bank. The group of commercial banks is

very heterogeneous and it is not possible to make any a-priori assumption on the effect of the

dummy variable on the probability of adoption of Internet banking with respect to this group of

institutions. Savings banks are generally more flexible than commercial banks and have a particular

attention towards customer needs and towards the development of new technologies that enhance

service functionality: therefore we expect these institutions to be particularly proactive in the

adoption of Internet banking. On the contrary, rural and trade banks have the statute of a co-

operative firm, are generally quite small and tend to be non-profit oriented organisations that

operate in a geographically limited context: in line with the descriptive analysis made before, we

expect these banks to be quite slow in the adoption.

The last explanatory variable take into account concerns the demand side of the market. In the

service sectors the introduction of innovations often occurs in response to users needs. The

possibility of accessing banking services 24 hours a day, without having to go to the branch,

constitutes a value-added function for the customers of a bank. However, the exploitation of

Internet banking services requires that the potential users are familiar with the Internet: therefore the

banks may consider the diffusion of the Internet within the population as a necessary pre-condition

for the success of Internet banking. Furthermore, although in principle the Internet could allow

banks to acquire new customers without the need to build a brick and mortar structure, Italian banks

- beyond few exceptions - operate in a well-defined geographical area and their customer base is

located in that region. For this reason, we consider the percentage of Internet users (home, work and

school users) over total population within a certain region (macro-region) as the potential market for

Internet banking services for a bank that operates in that area. According to the official statistics, the

distribution of Internet users over total populations in Italy is the following: 26.3% in the North

West, 26.1% in the North East, 28.3% in the Centre and 20.1% in the South. The most advanced

5 Beyond commercial banks, the Italian banking system includes also saving banks and cooperative banks. Savingbanks are retail banks and other similar financial institutions that generally have a significant share in their nationaldomestic banking markets, maintain broad national distribution channels and enjoy a common customer oriented and

regionally rooted banking tradition, acting in a socially responsible manner. Their market focus includes amongst othersindividuals, households, SMEs and local authorities. Their distinguishing feature is that they wish to cooperate withessentially similar types of bank internationally on cross border projects and issues that are of mutual benefit to the

retail banking industry, enable them to take advantage of combined strength and/or economies of scale in making acontribution to their respective profits. Cooperative banks are banking institutions that serve the cooperative business

community, both agriculture and consumer. These institutions were created in part to meet the financial needs of thecooperative community that were not being met by the traditional financial community.

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area in terms of Internet diffusion is the Centre, with the North West and the North East being quite

close, and the South being far behind. We introduce a dummy variable that indicates the potential

demand for Internet banking, assuming that the existence of a high percentage of Internet users acts

as an incentive for banks to adopt the technology. Therefore we expect that banks operating in the

Centre are stimulated to adopt quickly, while banks located in the South are slow to introduce

Internet banking services. Table 6.1 summarises the explanatory variables.

Table 6.1 Explanatory variables

Branch

Assets

Number of branches 1999

Assets 1999 - ITL million

Profit Profits 1999 - ITL million

Age Year of foundation

Intmarg Interest margin/Gross income

Branching Branches/Assets*1000Costhk Cost of personnel/Assets

Duminnov =1 if ATM/Branches >1

=0 otherwise

DumstatCOMM =1 if commercial bank

=0 otherwise

DumstatCOOP =1 if co-operative bank

=0 otherwise

DumstatSAV =1 if savings bank

=0 otherwise

DumregNW =1 if NorthWest bank

=0 otherwiseDumregNE =1 if North East bank

=0 otherwise

DumregCEN =1 if Centre bank

=0 otherwise

DumregS =1 if South bank

=0 otherwise

5. The sample of analysis and the specifications of the modelThe Web site of Nuova Banca di Credito di Trieste (http://www.nbctkb.it) lists all the adopters per

month since September 1995 together with the type of services they provide (informative Web

pages, home banking, trading on line, electronic commerce). It would have been interesting to carry

out an analysis of adoption for each different technological solution, but due to the scarcity of

adopters in some of these categories, we decided to put all the services (informative and

transactional Internet banking) together under the label of Internet banking for the econometric

analysis. With the information on the exact number and names of adopters by month, we chose to

investigate the probability of adoption by semester. Data on the explanatory variables were obtained

from three different and complementary sources: BANKSCOPE - a database which includes

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balance sheets data and ratings on about 10,500 world banks; the annual report on Italian banks

published by Milano Finanza (2000), a newspaper specialised in financial issues; the annual report

of the Italian Banking Association (2000).

The sample of analysis includes 698 banks, out of which 96 commercial banks, 60 savings banks

and 542 co-operative banks. We do not have any financial group in the sample. If we look at the

location of the banks, 117 banks operate in the North West, 277 in the North East, 130 in the Centre

and 157 in the South. It is important to notice that we could not categorise geographically 17

banks, whose activity is nation-wide. The failure event is the adoption of Internet banking: out of

698 total banks, 21 adopt the technology on enter time (second semester of 1995); of the remaining

677, 309 experience a failure (i.e. adopt) and 25% of them have a survival time of 6 semesters (3

years). If the incidence rate (i.e. the hazard function) could be assumed to be constant, it would be

estimated as .0567702 per semester, which corresponds to 0.1135404 per year. This means that in

each year, there would be a probability of 11% that adoption occurs, given that it has not yet

occurred in the previous year. All the data on the explanatory variables refer to 1999 6. Table 6.2

illustrates summary statistics.

Table 6.2 Summary statistics for the explanatory variables

Variable Obs. Mean Std. Dev. Min Max

Branch 698 4046.275 13000.48 100 129200

Assets 648 4265.702 20108.1 15.877 242409

Profit 697 14044.12 72155.02 -93476.5 1022303

Age 695 69.35827 89.62882 1 2000

Intmarg 697 .7664665 .2848755 .0599877 7.187097

Branching 648 2.449344 1.557126 .0063061 20.67291

Costhk 610 1.782668 .6004572 .3078829 8.520941

6 In order to estimate duration models of diffusion, one would need a data base on the life history of the population ofpotential adopters, together with detailed data about a new technology over a long period of time, beginning with theemergence of the innovation in the market. However it is quite difficult to find such data bases and it is commonpractice to sample a population of potential adopters at one point in time. This procedure may lead to sample attrition,since some firms may have closed down by the time of the sampling precisely because of the adoption of the new

technology. However, Karshenas and Stoneman (1993) demonstrate that the sample design is insignificant for

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Before performing the econometric analysis and testing the survival model of technology adoption,

it is useful to study the matrix of correlation of the explanatory variables.

estimation purposes, building a probability model of the exit times to account for the possibility of selection bias in the

sampling distribution of the model and rejecting the hypothesis of state dependence of exit time,.

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Table 6.3 Correlation matrix

Assets branch profit intmarg age branching costhk INNOV NW NE CEN S CO

Assets 1.0000

Branch 0.8901 1.0000

Profit 0.9063 0.8358 1.0000

Intmarg -0.0765 -0.1094 -0.0803 1.0000Age 0.0884 0.0634 0.0883 -0.0070 1.0000

Branching -0.1714 -0.1079 -0.1598 0.2070 -0.1008 1.0000

Costhk -0.0734 -0.0383 -0.0624 -0.1126 -0.0503 0.0004 1.0000

INNOV 0.1658 0.2001 0.1603 -0.1145 -0.0143 -0.2264 0.0014 1.0000

NW 0.1592 0.1449 0.1476 -0.1328 -0.0028 -0.1215 0.0651 0.1192 1.0000

NE -0.0749 -0.0612 -0.0365 0.0857 0.0209 0.0943 -0.1601 0.0015 -0.4055 1.0000

CEN -0.0131 -0.0173 -0.0177 -0.0261 0.0020 -0.0970 0.1078 0.0556 -0.2254 -0.4488 1.0000

S -0.0443 -0.0438 -0.0776 0.0454 -0.0261 0.0965 0.0311 -0.1745 -0.2146 -0.4273 -0.2375 1.0000

COMM 0.2122 0.2985 0.2268 -0.1389 0.0850 -0.1444 0.1387 0.0663 0.1735 -0.1821 -0.0074 0.0734 1.0

COOP -0.2485 -0.3331 -0.2346 0.1523 -0.1104 0.2164 -0.2323 -0.1658 -0.1566 0.1989 -0.1160 0.0160 -0.

SAV 0.1124 0.1355 0.0773 -0.0592 0.0600 -0.1419 0.1702 0.1569 0.0276 -0.0767 0.1685 -0.1021 -0.

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Table 6.3 confirms that there is a high correlation between the size variables - assets and branch -

and between these variables andprofit: branch and profit are slightly less correlated than assets and

profits, although the correlation becomes higher if we consider the size squared term. For this

reason, using the Coxs exponential survival model previously described, we decide to test two

different specifications of the model: in the first one we measure size as the total assets, in the

second one we measure size as the number of branches.

SP1: Pr (adoption in t | non adoption in t-1) = f (assets, profit, age, intmarg, branching, costhk)

SP2: Pr (adoption in t | non adoption in t-1) = f (branch, profit, age, intmarg, branching, costhk)

Both the specifications are tested with and without the size squared term. The dummy variables

concerning the degree of innovativeness, the region of operation and the corporate governance of

the bank are not included in the initial specifications, but are introduced in a second stage.

6. The results of the econometric analysisThe analysis is performed using maximum likelihood estimations, with a number of observations

equal to 586 in all the regressions, but in the ones including the dummy variables for the region of

operation, where we have 573 observations (for the reason previously mentioned).

Table 6.4 illustrates the results of the test. Specifications 1 and 3 include measure size as total

assets, while specifications 2 and 4 use number of branches. Specifications 1 and 2 include the

dummy variables of the demand, specifications 3 and 4 include the variables of corporate

governance. The hazard ratio identifies the coefficient under the proportional hazards assumption

that characterises the present model and represents also the differences between the banks due to

individual characteristics. The coefficient can be interpreted as the increase (if >1) or the decrease

(if

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subjects differing by one standard deviation by raising the hazard ratio to the power on one standard

deviation.

Table 6.4 The determinants of Internet banking adoption

SP1 SP2 SP3 SP4

Haz, Ratio z Haz, Ratio z Haz. Ratio Z Haz. Ratio z

Assets 1,000055(3,021989)*

4,53 1,000058*(3,20989)

5,11

Assets2 0,999998(0,474664)*

-3,43 0,999998*(0,40894)

-4,36

Branch 1,000067*(2,389306)

5,69 1,000062*(2,23895)

5,69

Branch2 0,999995**(0,576050)

-2,43 0,999996**(0,63275)

-2,28

Profit 0,9999979(0,859396)

-1,23 0,9999997(0,978586)

-0,15 0,999998(0,90392)

-1,07 0,999999(0,98567)

-0,15

Age 1,00082(1,076231)

1,46 1,000884(1,082417)

1,61 1,000511(1,04685)

0,82 1,00057(1,05240)

0,91

Intmarg 0,1886067* -3,58 0,227109* -3,06 0,182343* -3,72 0,187653* -3,57

Branching 0,8641198** -2,52 0,867371** -2,44 0,877971** -2,23 0,863608** -2,49

Costhk 1,381094* 3,48 1,374485* 3,22 1,292288** 2,47 1,279599** 2,25

Duminnov 1,731355* 4,16 1,674559* 3,91 1,603387* 3,71 1,573884* 3,57

DumregNW 1,245348 0,96 1,274981 1,06

DumregNE 1,115722 0,55 1,152695 0,71

DumregCEN 1,454971*** 1,76 1,520739** 1,97

DumstatCOOP 0,317237* -6,54 0,348471* -5,95

DumstatCOMM 0,3603538* -4,83 0,359590* -4,92

Note: the figures in brackets represent the rescaled coefficients.*Significant at 99% ; ** Significant at 95%

The probability of adoption of Internet banking is positively affected by the size variable, meaning

that large banks tend to adopt the technology more quickly than small banks, which confirms our

initial hypothesis. However, the coefficient of the size squared term is lower than one and

statistically significant. This result confirms our expectations on the role of medium banks as the

quickest adopters of the technology: indeed the positive relationship between size and the

conditional probability of adoption holds up to a certain size and then it becomes negative. The fact

that medium size banks tend to adopt Internet banking faster than large banks is partially explained

by the greater flexibility and smaller constraints of these institutions that are innovative and can rely

upon relevant financial resources, but do not invest heavily in physical infrastructure and do not

have to deal with a myopic and constraining legacy system. The profitability of the bank has a

negative effect on the adoption, but it is statistically insignificant, which is in line with the literature

(see Hannan and McDowell, 1984; Escuer et al., 1991; Buzzacchi et al., 1995). Similarly, there is

not a statistically significant relationship between the age of the bank and the probability of

adoption.

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A very interesting result is related to the characteristics of the activity of the bank: the interest

margin/gross income ratio seems to have quite a negative effect on the conditional probability of

adoption of Internet banking (the corresponding hazard ratio decreases significantly when intmarg

increases by one unit). We have already mentioned that a high ratio indicates a strong propensity

towards basic, interest income transactions. From the above results it seems that banks with a high

share of interest margin adopt the technology more slowly than banks that are engaged in different

types of financial transactions - e.g. brokerage - and this finding can be interpreted according to two

explanations. On the one hand, it is usually believed that banks with a high proportion of income

deriving from non-interest activities are more innovative than the others. This is because they have

aligned their business strategy with their technology strategy, so that core financial competencies

are strongly linked to the governance of technological assets. These banks tend to quickly adopt a

new technology, since they envisage the value-added of Internet banking for their overall business

and not just in terms of enhancement of the ICT functions. On the other hand, the average cost of a

financial transaction for the bank is quite different according to the specific transaction taken into

consideration. As mentioned before, an interest income activity is less expensive for the bank than a

transaction that generates non interest income. This means that the cost reduction deriving from the

adoption of Internet banking is much higher for banks whose activity is biased towards non interest

income transactions than for banks with a high interest margin/gross income ratio. Therefore these

banks have more incentives to adopt these technological systems.

Another remarkable finding concerns the role of branching intensity in affecting the conditional

probability of adoption. The coefficient indicates that banks with a high branching intensity adopt

more slowly than banks with a more flexible and leaner branch structure. This relationship supports

the idea that having built a branch structure is perceived by banks as a sunk cost and this investment

tends to retard the adoption of Internet banking. Furthermore, an intense branch structure indicates

also the existence of a well-established relationship with the customers and this means that banks do

not see the need for investing in new technologies in order to provide enhanced services. According

to this line of reasoning, it is possible to say that this technology is considered by the financial

institutions more as a substitute than as a complement to the existing system of service delivery.

However, Internet banking should not be conceived as an alternative technology to the existing one,

but as a complementary technological and organisational system, which helps banks find new ways

of delivering their existing services and of developing innovative services.

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The evidence of a positive relationship between the cost of human capital and the adoption of

Internet banking is also quite strong. Table 6.4 shows that the hazard ratio of the variable costhkis

greater than one and significant, meaning that if a bank bears considerable personnel costs, it will be

more induced to adopt Internet banking than a bank that does not incur in such expenditures. Our

initial hypothesis, based on the consideration that, at least in the short term, the adoption of Internet

banking causes a reduction of the costs of human capital, finds confirmations. However, it is

important to remember that this technology has appeared quite recently in the market and therefore

banks still perceive its short term advantages. In the long run, it is quite likely that there will be the

need for new professional figures and new experts both in the ICT and in the financial area:

therefore, the diffusion of Internet banking is probably going to raise the cost of human capital

within the banking industry.

Among the dummy variables, the first factor we consider is the attitude of the bank towards

innovation. The test of the specifications shows clearly that there is a positive relationship between

the propensity to innovate and the conditional probability of Internet banking adoption, as we had

previously assumed. This is in line with the idea that the development and adoption of ICT-based

technologies require a set of competencies that can be accumulated only through an incremental

learning process, from the most simple forms of automation, to the more complex Internet-based

systems. Although the relative number of ATM is not the most appropriate indicator of

technological intensity, it nonetheless represents an important factor in identifying the diffusion of

ICT in a bank7.

The second factor we examine through the introduction of a dummy variable is the relevance of the

demand context in which banks operate. In particular, we want to investigate if the existence of a

potential demand for Internet banking services is conducive to the adoption of this technology and

in doing so, we consider the number of Internet users in the region of operation of the bank as the

potential demand, assuming that these users will be more inclined to utilise Internet-based financial

services. In order to avoid problems of multicollinearity, we test the two specifications 1 and 2 by

introducing three regional dummy variables.

If we consider the three regional dummy variables (dumregNW, dumregNE, dumregCEN), we find

that the coefficients of dumregNW and of dumregNE are statistically insignificant, while the

coefficient ofdumregCENis greater than one and statistically significant (although in specification

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1 the level of significance is quite low), meaning that if a bank operates in the Centre, its

conditional probability of adoption increases with respect to banks operating in the South. We have

already mentioned in the first part of the chapter that the Centre is the geographical area in Italy

with the highest percentage of Internet users over total population, while the South is at the bottom

of the ranking. The econometric analysis indicates that the potential demand has a role in

determining the adoption of Internet banking by financial institutions, although the results are not

very robust. The relationship we find with respect to this specific innovation confirms the

importance of the demand context as a driver of adoption of new technologies in the service sectors.

However, the scarce significance of this dummy variable for the other two regions suggests also

that, in the case of Internet banking, the supply-push forces are much stronger than market pull

factors, at least in the initial phases. In other words, it is reasonable to argue that the adoption of

these technological systems, at least in the initial phase, has been determined more by banks

strategies to face the competition of rivals than by the need to meet existing users requirements.

The last issue concerns the relevance of the statute of the bank in determining the probability of

adoption of Internet banking. The relationship between the type of corporate governance and the

adoption of Internet banking is negative and statistically significant for commercial banks and for

co-operative banks. This means that the conditional probability of adoption of Internet banking is

lower for these two types of institutions as compared to savings banks. We had already mentioned

that savings banks have been the fastest adopters of Internet banking, followed by commercial

banks and by co-operative banks. The econometric analysis confirms this evidence, by showing not

only that the hazard ratio is lower than one for these two groups of banks, but also that the

conditional probability of adoption is lower for co-operative banks than for commercial banks. This

finding verifies our initial hypothesis that co-operative banks are not very inclined to adopt Internet

banking, because their activity is very much concentrated on basic financial transactions - loans and

deposits - and because they usually have a small and local customer base. As far as savings banks

are concerned, they are more likely to adopt Internet banking technological systems than other

institutions, because they generally aim at offering innovative services to their customers and are

less inertial than big commercial institutions towards the adoption of new technologies. However,

the scarce propensity to adopt the innovation shown by commercial banks as compared to savings

banks should be taken into consideration with some caution, since this group of institutions is quite

heterogeneous and includes many different banks, some of which have had a leading role in the

process of diffusion of technological systems in the sector.7

Indeed, most of the studies related to the diffusion of new technologies in the banking industry have investigated theadoption of ATM as the most significant ICT-based innovation.

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7.Summary and conclusionsThis paper has aimed at throwing light on a recent and not well-investigated phenomenon, i.e. the

adoption of Internet banking. In particular, the objective has been to investigate the relationship

between Internet banking and the traditional banking activity, in order to examine the degree of

substitution/complementarity between these systems as perceived by banks. The focus of the study

has been the Italian retail financial service sector and the research has concentrated on the

determinants of adoption. We propose here a summary of the most significant results we have

obtained from the econometric analysis. In doing so, we provide at the same time some conclusive

remarks on the pattern of adoption of Internet banking technology within the Italian banking sector

and we elaborate a possible future scenario for the diffusion of the on-line financial services.

7.1Summary of the results: the determinants of Internet banking adoption

The present analysis represents one of the first attempts to investigate the determinants of the

adoption of Internet technology for the provision of banking services in the Italian context and it is

an innovative piece of work in that it examines the entire population of Italian banks. Relying upon

a well-established econometric technique (duration/failure time models) for testing models of

adoption-based diffusion of innovations, the study introduces a relevant number of explanatory

variables, in order to understand their role in determining the adoption of new technologies by

banks. The research generates important results concerning the determinants of adoption. In some

cases, the results reinforce or contradict the findings of the previous literature on the diffusion of

new technologies in the banking sector, in other cases they offer new evidence on the impact of

specific variables on the probability of adoption.

First, we find that the conditional probability of adoption of Internet banking is positively affected

by size; however, while the coefficient of the size term is positive, the coefficient of the size

squared term is negative, meaning that medium banks tend to adopt more quickly than large banks,

mostly because they have a more flexible structure and lesser constraints than big financial

institutions. This result is quite new, since the literature does not find a significant non-linear

relationship between the adoption of a new technology and firm size.

One of the most important results concerns the role of the investments in physical infrastructure and

human capital in explaining the pattern of adoption of Internet banking. The intensity of branching

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negatively affects the probability of adoption of this technology, meaning that the existence of a

branch structure is perceived as a sunk cost by the banks and that the brick-and-mortar

infrastructure is still seen as the best way to maintain the contact with the customers. This finding is

crucial, since it implies that banks perceive this technological system as a substitute more than as a

complement to their existing branching structure. As we have mentioned before, other works have

found a similar result with reference to the adoption of ATM, but the finding appears to be quite

relevant in this specific case.

With respect to the costs of personnel, we find that they are positively related to the probability of

adoption, and this indicates that if a bank faces considerable expenditures in human resources, it

will be more inclined to adopt the technology (in order to reduce these costs). Once again, this

result seems to support the idea that there exists a relationship of substitution instead of

complementarity between Internet banking and the traditional banking system, since it implies that

banks see the new technological platforms as a means to reduce the need for human capital, without

considering that the implementation of the new system requires the employment of new

professional figures (especially Internet experts) and the re-training of the existing ones.

Another important result concerns the role of the activity of the bank: we show that a high interest

margin/gross income ratio negatively affects the adoption of Internet banking. Banks with a high

proportion of income deriving from non-interest activities provide more complex and value-added

(innovative) services and tend to adopt new technologies more quickly than other banks. This is

because they are forward-looking institutions that have aligned their financial competencies with

their technology strategy and consider Internet banking as a crucial component of their overall

business. Furthermore, the average cost of a financial transaction for the bank is lower for an

interest-based transactions than for a transaction that generates commission income. This means

that the cost reduction deriving from the adoption of Internet banking is higher for banks whose

activity is biased towards non-interest income transactions and therefore these banks have more

incentives to adopt the new technological systems.

There is a positive relationship between the propensity to innovate and the conditional probability

of adoption and this is in line with the idea that the development and adoption of ICT-based

technologies require a set of competencies that can be accumulated only through an incremental

learning process. This is in line with other similar findings in the literature: here we chose a new

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indicator for the propensity to innovate of banks (ATM/Branches), but future research should

concentrate on the development of more appropriate indicators to account for this characteristic.

The demand context appears to be a significant variable in shaping the process of diffusion of

Internet banking, although the level of significance is not very high and the result is not very robust.

The fact that banks operating in the Centre have a higher probability of adopting Internet banking

systems than banks in the South partially confirms that the existence of a potential customer base

may constitute an incentive for banks to offer value-added Internet services, considering that this

area has the highest percentage of Internet users over total population. This is the first attempt to

include a variable which accounts for thepotentialdemand in works related to the adoption of new

technologies in service sectors and the results suggest that the issue is quite relevant. We believe

that there is the need for future investigation on the topic and particularly on the co-evolution

between the dynamics of the demand context and the development and diffusion of innovations in

the service sectors, especially with reference to ICT-based innovations.

Finally, the statute of the bank is quite important in affecting the conditional probability of adoption

of Internet banking. In particular, we find that savings banks tend to adopt quicker than commercial

banks and co-operative banks, the latter being the slowest adopters of Internet banking. This is a

very important result, which we suspect does not apply exclusively to the Italian case, and is also

quite new, at least in the context of research on the banking sector. Previous empirical studies based

upon the applications of duration techniques have generally investigated the role of corporate

governance in terms of public vs. private ownership, but the differences between banks have not

been analysed before.

7.2Conclusions and prospects for future research

Internet banking constitutes a radical service innovation in the financial sector: the radical

characteristic of such an innovation lies in its potential for changing the technological,

organisational and market context in which banks operate. They face the opportunity to enormously

increase the value of the services they offer to the end users, while, at the same time, gaining long-

term efficiency in terms of economies of scale and scope. The main issue for banks is to understand

the real value of the innovation, which is not a substitute of the existing structure, but represents a

means of increasing its flexibility and, at the same time, a way of widening and customising the

range of services provided on the market.

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From the results of the empirical analysis, banks seem to perceive Internet banking as a substitute

for the existing branching structure, although there is also some evidence that banks providing

innovative financial services are more inclined to adopt the innovation than traditional banks. Due

to the fragmentation of the banking system in Italy, with more than two thirds of financial

institutions being constituted as co-operative banks, the adoption of Internet banking has so far

concerned slightly more than half of the total population and the low intensity of adoption, in terms

of the complexity of the services offered, suggests that there is still a great opportunity for the future

diffusion of these technological systems. The relatively recent appearance of the innovation in Italy

can partially justify the scarce demand for new Internet-based services (around 10% of the existing

customers) and the scepticism of some banks towards the adoption of Internet platforms. So far the

introduction of Internet banking has been driven more by the willingness of the banks to be

competitive on the market with respect to new entrants and innovative institutions than by the

emergence of specific needs from the demand side.

In this context, the fact that early adopters have been savings banks, that are traditionally oriented to

satisfy customers requirements, might suggest that a certain interest from the end users towards

these applications is emerging. In the future, it is likely that banks will be more active in the

provision of Internet-based financial services, while, at the same time, they will renovate their

organisational structures in order to harness the potential of new technologies to increase their

competitiveness. However, the success of Internet banking will impinge upon the interplay between

technology and marketing strategies of financial institutions and market requirements, and it is

reasonable to argue that banks will need to develop an incentive structure for the end users, in order

to stimulate the diffusion of new services.

Further research is needed in order to identify more specific issues regarding the adoption of

Internet banking in the financial sector in general and the pattern of diffusion of such innovation

among banks in Italy. One of the most important issues is the analysis of the intensity of adoption,

in terms of the complexity of the services provided by different categories of banks. In this respect,

it would be useful to carry out an econometric analysis which takes into account different types of

Internet based services and applications and the pattern of adoption across different categories of

banks. Furthermore, once data on the demand side of the market will be available, the investigation

of the role of customers on the adoption of such innovation would add valuable information about

the phenomenon.

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