INTRODUCTION

Over the last two decades, the financial industry has undergone dramatic changes due to the integration of technology into its operations. New technologies are expected to provoke important changes both in customer behaviour^{1, 2} and in the channel structure of banking distribution system.^{1, 3 and 4}

Specifically, the use of voice, electronic and network technologies have opened very promising opportunities for financial service companies to add alternative distribution channels, like phone, mobile, television or internet banking, in addition to the already well-established ATM channel. These channels constitute a key means of differentiation⁵ and the channel mix decisions are considered complex but also critical marketing decisions.^{4, 6}

Research focusing on the adoption of such technology-based channels by customers has underlined the important role of trust in the acceptance and use of these channels.^{7, 8, 9 and 10} In spite of the growing literature on this role of trust in the context of electronic and innovative channels, however, little attention has been paid to the specific construct of trust in a channel as well as to its antecedents.

Particularly, when studying trust towards new, technology-based channels of an existing company, which is not a pure online player, one should consider trust in the channel as a different and distinct construct from trust in the company. Furthermore, trust in the existing, well-known to the customer, offline company could be hypothesised as a variable influencing the trust in a new channel of this company, as one could expect a 'transfer' of trust from the company towards its new channels.

To our knowledge there is very limited research that has addressed the issue of this relationship, or transfer, of trust from a company level to a channel level, especially in the context of technology-based distribution channels. A relatively recent e-banking study¹¹ has measured the variables of trust in the electronic channel and trust in the bank, however the latter variable was tested as a predictor of the adoption of e-banking and not as an antecedent of trust in the e-channel. Based on this background and trying to fill the gap in the construct of trust towards a channel and its relationship to trust towards the 'parent' company, the objective of the present study was two-fold:

1. to adapt and test the definition and measures of trust in the specific context of technology-based channels, and
2. to investigate the role of trust in the 'parent' company in forming trust in its new, technology-based channels.

CONCEPTUAL FOUNDATIONS

Trust is a very important factor for new technologies adoption¹² including the WWW and e-commerce.¹³ It is a very critical factor in e-commerce since it is supposed to reduce the social complexity for the e-consumer¹⁴ and drive to the achievement of e-goals,^{15, 16} and without it there is a failure of such goals and relations.^{17, 18} The fulfilment of promises and the development of high-level cooperation is believed to enhance trust.¹⁹ On the opposite side, trust reduces because of the absence of consistent and reliable behaviour.²⁰

Trust and risk are among the most important antecedents for online shopping^{21, 22 and 23} and an essential element for relationship marketing.²⁴ Despite this work, there is limited empirical evidence on how it is formed and structured in an online context.²²

Trust in general has been given many different definitions, depending on the various angles through which it has been analysed in different disciplines and on the different dimensions that it may include.^{16, 25} The various dimensions and the role of trust have been examined by disciplines such as economics,^{26, 27} sociology,^{16, 28} social psychology^{29, 30} and marketing.^{31, 32 and 33} Because of the multidimensionality of the meaning of trust and its dynamic role, there is no consensus on its definition by the various disciplines and researchers.^{16, 34}

Building on a synthesis of the conceptual and empirical work on trust adapted to an electronic context, McKnight et al.³⁵ and McKnight and Chervany⁷ have suggested a definition of the construct that covers more than 90 per cent of the 65 most important papers and books on the subject. This conceptualisation describes trust through four distinctive components: Competence, one's belief that the other party has the ability or power to do what needs to be done; Benevolence, one's belief that the other party cares about and is motivated to act in one's interest; Integrity, one's belief that the other party makes good-faith agreements, tells the truth, acts ethically and fulfils promises; and Predictability, one's belief that the other party's actions are consistent over time and can be forecasted in a given situation. Given its wide scope, this definition was adopted in the present study.

Considering the specific construct of trust in a distribution channel, the literature typically refers to the traditional (offline) relationships between a company and the members of its channels.^{31, 36 and 37} Specific work on trust in electronic channels has mainly focused on online stores (pure online retailers).^{8, 9, 10, 13 and 38} Other empirical studies refer to relationships between members of a channel in horizontal or vertical traditional distribution systems^{31, 39 and 40} or to the relationship between the company and its salesmen.^{41, 42}Thus, it can be argued that trust towards the channels, and especially to e-channels, as a distinct construct from trust towards the company, has not been clearly defined and measured.

As far as the antecedents of trust are concerned, literature has suggested two categories of variables, one customer-specific and one company-specific. Among the individual characteristics that influence the level of trust, one of the most commonly used is the disposition to trust, one's positive or negative disposition to trust other people or entities even in the context of low information available to them.^{35, 43, 44, 45 and 46} Disposition to trust has been examined and confirmed as a factor that explains a part of trust, specifically in the case of internet and e-commerce.^{10, 13, 47, 48 and 49} McKnight et al.⁵⁰ were the first to study 'Disposition to Trust and not to Trust' relating to e-commerce services.

Among company-specific variables, reputation has proved to be a significant predictor of trust in both traditional^{31, 33, 42 and 51} and electronic channels.^{7, 8, 52 and 53} It is worth noticing that reputation has been examined in most studies from a 'trust' point of view, since researchers measure honesty beliefs, benevolence beliefs and competence beliefs. From that point of view, it is very logical to observe a strong relationship between Reputation and Trust.

As mentioned above, in the case of an existing bank that introduces new, technology-based distribution channels, one should consider trust in the channel as a different and distinct construct from trust in the bank itself. Furthermore, trust in the bank already known to the customer could be hypothesised as a variable influencing the trust in a new channel of this company, as one could expect a 'transfer' of trust from the bank towards its new channels.

There is extremely limited research that has addressed the issue of this relationship, or transfer, of trust from a company level to a channel level, especially in the context of technology-based distribution channels. Kim and Prabhakar¹¹ have conducted a study on e-banking adoption including the variables of trust in the electronic channel and trust in the bank, however the latter variable was tested as a predictor of the adoption of e-banking and not as an antecedent of trust in the e-channel. Their results supported the influence of trust in the e-channel to the e-channel adoption but no direct link was found between trust in the bank and the adoption of the e-channel.

RESEARCH MODEL AND HYPOTHESES

In this context, and attempting to fill the gap in the construct of trust towards a channel and its relationship to the trust towards the 'parent' company, the present research was designed to study the influence of trust in the bank, reputation of the bank and disposition to trust on trust in technology-based channels. Figure 1 presents the suggested research model.

Figure 1.

Research model: The trust building model in alternative channels

Full figure and legend (10K)

Although literature reviewed in the previous section has not made a distinction between trust in the bank and trust in its channels, we can assume that the two already established trust antecedents, reputation and disposition to trust, impact trust at both bank and channel levels. Additionally, the model tests the role of trust in the bank as an antecedent for trust in the channel, hypothesising a direct and significant effect.

Henceforth, five research hypotheses have been formulated:

H₁:

Disposition to trust has an influence on trust in the company

H₂:

Disposition to trust has an influence on trust in the channel

H₃:

Reputation has an influence on trust in the company

H₄:

Reputation has an influence on trust in the channel

H₅:

Trust in the company has an influence on trust in the channel

RESEARCH DESIGN AND METHODS

In order to test these hypotheses a large-scale survey was designed, sponsored by the Federation of the Greek Banks. With the collaboration of the top six Greek banks, 762 bank customers were personally interviewed inside 20 branches of the six banks in the Attica region, Athens, Greece. Interviews were conducted by postgraduate students, specifically trained for this survey.

The branches of each bank were randomly selected, with the number of branches per bank being proportional to the assets represented by the bank to the total banking assets. The interviews were conducted within a 15-day period, during customers' waiting time, and covered the total range of bank's opening hours.

Before the field research, a pilot study was conducted in order to test both the questionnaire and the customer approach. The final response rate was 13.4 per cent and the average time of the interview 23 minutes. The study focused on internet and phone banking, these two channels being in their introduction stage in the Greek market and receiving most of the attention and effort from Greek banks. In addition, ATMs, the main current electronic channel, used by a large majority of bank customers, were included in the study in order to serve as a point of comparison with the two new, unfamiliar to the respondents, channels.

Respondents were filtered to be users of ATMs but nonusers of internet and phone banking. The sample proved to be globally representative of the bank customers of Greek bank users population.

The measures and their validation

Trust in the company was measured using the scales validated in previous research.^{7, 42 and 54} Items for trust in the channels were adapted from those of trust in the bank. Disposition to trust was measured on scales used in previous studies on e-commerce.^{13, 54} Reputation was measured using existing scales⁴² to which we decided to add three items referring to the bank's reputation in serving customers through its channels. For all measures a seven-point Likert scale was used. Measurement items are shown in the appendix.

Because, as mentioned above, some scale items were adapted to the specific context of the research, an exploratory factor analysis (EFA) was first run. The EFA used the Principal Component extraction method, followed by a Varimax rotation⁵⁵ and revealed the following results:

1. The four dimensions of trust were grouped into two new constructs, the first one being the merging of 'competence' and 'predictability', and the second the merging of 'benevolence' and 'integrity'. These two new constructs can be named 'cognitive' and 'affective' trust, respectively, as mentioned in some studies in the literature.^{16, 56} For the 'Bank Trust' construct, four items on the 'affective' dimension of trust (two from 'benevolence' and two from 'integrity'), and two items on the 'cognitive' dimension (both from 'competence') showed about equal share of variance on the two factors and for this reason they were excluded from further analysis. For the 'Channel Trust' construct, two items on the 'affective' dimension of trust (one from 'benevolence' and one from 'integrity'), and one item on the 'cognitive' dimension (from 'competence') were excluded from further analysis for the same reason. The same factors were formed in the case of ATMs, internet and phone banking.
2. The 'Reputation' construct formed two factors, the 'General Bank Reputation' and the 'Bank Channel Reputation', with two items excluded from further analysis (one from each factor).
3. The 'Disposition to trust' construct formed one distinct factor.

Following these results, a confirmatory factor analysis (CFA) was run, using the structural equation modelling (SEM),^{57, 58} in order to purify the measures employed in this study, examine the dimensionality of the scales and assess their psychometric properties. Table 1 presents these results:

Table 1 - Confirmatory factor analysis results.

Full table

All goodness of fit indices and psychometric properties of the scales are within the accepted levels,^{55, 59} except the four bold indices of discriminant validity referring to the two dimensions of trust. These latter constructs were then reconfirmed by comparing the one, two and four dimensions' scenarios, the analysis showing the better fit for a two dimension construct. Disposition to trust does not appear in the table because it was measured with only three items; its reliability was 0.88 and its convergent validity 0.71.

RESULTS AND HYPOTHESES TESTING

In order to test our hypotheses, data were analysed through SEM, using AMOS 5.0 software. The indices are presented in Table 2 and the structural models with the regression weights for each channel are depicted in Figures 2, 3 and 4 below:

Figure 2.

Results of the trust building model for ATMs

Full figure and legend (26K)

Figure 3.

Results of the trust building model for internet banking

Full figure and legend (26K)

Figure 4.

Results of the trust building model for phone banking

Full figure and legend (25K)

Table 2 - Goodness of fit indices (after modifications).

Full table

All indices for all channels present very good fit to the data.⁵⁵ Observing the results of the hypothesis testing, we can conclude that:

1. H₁ and H₂ are partially accepted as 'Disposition to Trust', affects only the 'Affective Bank Trust' and the 'Affective Channel Trust' for internet and phone banking, although, in the case of ATMs, it affects the 'Cognitive Bank Trust', the 'Cognitive Channel Trust' and the 'Affective Bank Trust'. (Figure 4)
2. H₃ and H₄ are also partially accepted as 'General Bank Reputation', affects only the 'Affective Bank Trust' in both internet and phone banking, while, in the case of ATMs, it affects the 'Affective Bank Trust' and the 'Cognitive Bank Trust'. The 'Bank Channel Reputation' affects both dimensions of 'Bank Trust' and the 'Cognitive Channel Trust' for the two innovative channels, but for ATMs it affects the two 'Cognitive' dimensions of 'Bank Trust' and 'Channel Trust'.
3. H₅ is partially accepted, as only the 'Affective Bank Trust' influences the 'Affective Channel Trust' for all electronic channels, while, in the case of ATMs, 'Cognitive Bank Trust' influences the 'Cognitive Channel Trust'.

It is very interesting to observe that patterns of relationships among variables are the same for internet and phone banking, with different regression weights, but quite different between these two channels and the most established electronic channel, that of ATMs.

DISCUSSION AND RESEARCH CONTRIBUTION

These results allow a better understanding of the structure of trust in a channel. First, to our knowledge, no previous research has addressed the two constructs of trust in the company and trust in its channels separately or investigated their respective components. It is worth reminding that trust has been examined in the four dimensions of 'benevolence', 'integrity', 'competence' and 'predictability' according to the interdisciplinary typology of trust.^{7, 35} The 'benevolence' and 'integrity' components formed the construct 'affective trust' and the 'competence' and 'predictability' components formed the construct 'cognitive trust'. The two dimensions of affective and cognitive trust are an important finding and contribution, since although these two dimensions are mentioned by some authors in different settings, such as social context, business-to-business relationship and company–employees relationships,^{16, 56, 60 and 61} they were not identified as such in the case of company and channel trust.

Secondly, the relationship between trust in the company and trust in a company channel (particularly a technology-based one) has not been investigated either. Revealing the links between the two constructs leads to important implications for both academics and practitioners. The 'transfer' of trust from a company to its channel level enriches the understanding of how trust in a channel is formed, especially in the case of existing companies that add such channels in their existing operations. The affective component of trust in the bank proved to be the most important predictor of trust, especially in the phone and internet channel, and seems to form more particularly the affective trust to these channels. The cognitive component of trust in the bank is transferred only in the case of ATM's trust, the channel that the respondents were already using. This specific result can lead to the conclusion that in new and unknown circumstances such as the new and innovative channels, someone decides to trust them with the affective part of trust, especially if he believes that his bank is benevolent and fair. This finding is consistent with previous work,⁷ suggesting that affective trust is more important when someone does not know the object of trust.

Last but not least, the relations among the variables are the same in the case of internet and phone banking, but a little different in the ATM's case. The first main differentiation concerns the transfer of the affective and cognitive trust, mentioned above. The other one concerns the role of reputation. This variable is the second in importance for shaping trust in the channel after its discrimination to 'bank channel reputation' and 'general bank reputation', which is a new finding. Based on this finding, in the two innovative channels, bank channel reputation has a direct effect on cognitive trust while general bank reputation shows an indirect effect, through the channel reputation and a direct effect on the affective part of bank trust. The personal characteristic of disposition to trust shows a significant but weak effect on affective trust in the channel when referring to the new channels. This seems to imply that trust in the new channels is not so much person-dependent but rather based on the person–bank existing relationship. In the ATM channel, this personal characteristic shows a weak direct effect on the two dimensions of bank trust and a quite strong one on the cognitive channel trust, as a result from the experience of its use.

MANAGERIAL IMPLICATIONS

From a managerial point of view, since banks — but also many other service companies — use traditional and new channels in parallel and as technology opens more and more opportunities for new channels to be used, managers need to understand how to build trust in these channels. The identification of the two distinct components of trust, the affective and the cognitive one, and the different way they are transferred from the bank to the new channels will allow bank executives to not only measure trust in a more accurate way but also, more importantly, to design specific actions targeted to develop trust.

The results of the present study revealed that the affective trust in the bank is 'transferred' as affective trust in the channel. Consequently, banks having developed their corporate 'affective trust capital' (in terms of security, integrity, fulfilment of promises, fair treatment and transparency) can expect their customers to trust the e-banking and phone banking channels in a similar way. Further investing in these bank's attributes will also benefit the new channels. Specifically, managers should first build the affective trust through transparency, fairness, keeping promises, adapting their services to the needs of customers and establishing polices that create to the customer a sense of security and nonexploitation.

At the same time, other means, such as information, communication or demonstrations, should be used to develop cognitive trust beliefs in the channel (in terms of speed, effectiveness, problem solving, consistent attitude and consistence of procedures). In the case of these attributes it seems that new channels do not benefit from general bank perceptions and thus need specific actions to develop their own credibility. In this line of action of customers' information and education about the new channels, an important role may be played by the branch staff. Established relationships with, and trust in, the front-line personnel can be transferred to the alternative channels. Such synergies between offline (or traditional) and online (and more broadly new technology-based) channels and means will certainly prove to be an effective way for banks to optimise their channel-mix strategy.

LIMITATIONS AND FURTHER RESEARCH

Despite the large scale of this research, its findings are subjected to a certain number of limitations. The first limitation refers to the target group of the research. This empirical study targeted the retail bank customers who visit the branches and use the ATMs but not any other alternative bank channel. This means that the results are representative of the retail bank customer population with the exception of the (low) percentage of bank customers that use the alternative channels. A second limitation is geographical. The results are representative of the Greek region, but they cannot necessarily be generalised to other countries with different cultures and attitudes towards the acceptance of alternative bank channels. A third limitation refers to the variables that were included in the conceptual framework as antecedents of trust and the three technology-based channels that were examined by this research.

Based on the findings, further research could validate relationships in the context of other channels (television, mobile, etc), of other sectors (tourism, retailing) and in other countries. In addition, the reputation construct and its components can be further investigated as well as more antecedents (such as perceived risk, familiarity, innovation, etc) could be tested in order to better explain trust in the channel building process. A further confirmation of the scales that measure the affective and cognitive dimensions of trust could also be tested, in order to cross-validate the reliability and validity of the new scales. Finally, a next step would be to link trust in the bank and trust in the channel to willingness to use these technology-based channels in order to predict the new channels' use.

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Appendices

APPENDIX

Measures of constructs used in the questionnaire (translated from Greek)

See Table A1

Table A1.

Full table