INTRODUCTION

Relationship banking, which entails customers satisfying most of their financial needs with a single provider,^{1, 2} is fast becoming the fundamental success factor³ in the financial services market. The change from transactional to relationship banking has been stimulated by a number of driving forces,⁴ among which are the increasing sophistication of customers, the high level of market dynamism, the intensity of competition, and disintermediation.⁵ At the same time, banks' core businesses of money transmission and lending have become less profitable. Factors such as rising operating costs, reduced levels of consumer spending, narrowing lending spreads, market saturation, and adverse market conditions, all result in lower profits for financial institutions, which are being forced to rethink their marketing strategies.^{1, 6}

Under these conditions, financial providers are concentrating their efforts on the development of relationships with their customers.⁷ Relationship development efforts aim to increase the length, depth and breadth of relationships.⁸ The length refers to the duration of the relationship,⁹ the repurchase of the service, or else customer retention;¹⁰ the relationship depth refers to the level of service usage, that is, how much customers use the service;^{10, 11} while relationship breadth has to do with the number of services from the same provider that the customer acquires/uses (cross-buying). Banks try to stimulate relationship length and depth and are particularly focusing on cross-selling, in an effort to increase the breadth of the relationship with each customer, that is, the average number of services sold to each individual.^{12, 13}

Understanding the motivations of consumers that lead them to reduce their market choices and engage in a relationship with an organisation is therefore important both for practitioners, in order to manage their relationship development efforts better, and academics, in order to develop an effective theory of relationship marketing.¹⁴ Especially in the context of financial services, which are high in credence qualities, resulting in increased uncertainly, higher levels of perceived risk, and higher proclivity for relationship development, there is a need for conceptual frameworks on the nature and determinants of relationships.¹⁵

Extant literature focuses on relationship depth and length, but little research has been carried out to examine the factors that make customers buy additional services from the same provider.¹⁶ Many researchers, such as Beatty et al.,¹⁷ Hallowell,¹⁸ Bolton,⁹ Gwinner et al.,¹⁹ and Selnes,²⁰ studied the antecedents of customer retention and relationship duration, while others (see Goode et al.,²¹ Hallowell,¹⁸ Van den Poel and Leunis,²² Bolton and Lemon,¹¹) only examined the factors that affect the full use of a service. Far fewer studies (such as Bolton et al.,⁸ Ngobo,²³) deal with the cross-buying construct. The question of why customers decide to cross-purchase and enhance their relationship with the firm has not been adequately investigated in the literature.²³ Most importantly, the majority of previous studies have only implied the relationship between potential factors and cross-buying: there have been hardly any established links confirmed by research data. There is therefore a significant gap in our understanding of the factors that drive cross-buying behaviour, necessitating further evidence and conceptualisations in this area.¹⁶

The purpose of this study is to address this research gap by developing and testing a research model that combines some of the key variables that have been suggested in previous studies to impact the intention of cross-buying financial services, providing statistical evidence for both the relationships between these variables and cross-buying intention and the relationships among these variables. The selected context for this study is retail banking. Structural equation modelling is used for the analysis of the data collected via a survey of retail bank customers to test the proposed model. This was considered to be the optimum method of analysis, as it enabled the test of several dependence relationships simultaneously,²⁴ considering simultaneous equations with many endogenous variables.²⁵ Other multivariate methods of analysis could examine only one relationship at a time and use a limited number of variables.^{24, 26}

The rest of the paper is organised as follows. Extant literature on the factors that affect cross-buying intention, directly or indirectly, is reviewed to identify the key constructs related to cross-buying. The proposed research model is presented next, followed by the methodology employed to test it. The results are subsequently presented and analysed. The paper concludes with the discussion of the implications of the study.

CROSS-BUYING IN FINANCIAL SERVICES

Cross-buying behaviour is expressed as the number of different products bought/owned through the same provider.^{27, 28} It is complementary to cross-selling, which pertains to the supplier's efforts to increase the number of products or services that a customer uses within a firm,²⁹ In fact, cross-selling and its benefits can only be achieved if consumers are willing to cross-buy.³⁰ Verhoef et al.²⁷ were the first who introduced the term 'cross-buying' in their 2001 study, defining it as the number of different services bought from the same provider (breadth of the relationship).

Cross-selling focuses on the supplier's intentions and practices to interest the buyer in additional products or services from their product/service range. Cross-buying looks at the customer and refers to the customer's practice or intention of buying additional products and services from the existing service provider in addition to the ones s/he already has.²³ Customers may reject cross-buying offers because they do not want to be tied to one single service provider for a long time.²³ There are also customers who prefer to buy from a number of different financial service providers rather than to rely on one single provider, in an effort to spread their business, to diversify their risk, and to feel more secure.^{31, 32 and 33} Even so, there are also customers who demand several products from one single outlet.³⁴ According to Coughlan³⁵ and Ngobo²³ the key drivers of cross-buying are associated with the benefits of one-stop shopping.

A number of factors, which may affect bank customers' cross-buying decisions, have been proposed in previous research studies. Crosby et al.²⁷ focused on the customers' perceptions of salespersons' attributes and examined how these impact account penetration, customer retention, and cross-selling. The results showed that the salespersons' image, or else the customer's perceptions of a salesperson's similarity and service domain expertise, is directly related to high overall sales volume, the number of different products owned per customer, and customer retention. Crosby et al.²⁷ however, examined only the impact of perceived employees' attributes and behaviours on cross-sales.

Storbacka et al.³⁶ suggested a dynamic approach to relationship quality and developed a conceptual framework that incorporates the concepts of perceived value, customer satisfaction, relationship strength, relationship longevity, and relationship profitability. According to their model, customer satisfaction influences positively the strength of the relationship with respect to both purchase and communication behaviour. Relationship strength affects customers' perception of alternatives, their perception of critical episodes, and relationship longevity, which then impacts cross-buying. Storbacka et al.'s³⁶ study linked a number of different variables together and provided a holistic view of the factors that affect cross-buying and relationship profitability. Their model was, however, not tested in order to identify which of the hypothesised relationships hold.

Bendapudi and Berry³⁷ also developed a conceptual framework, which depicts the variables that lead to relationship breadth. According to their model, providers' expertise and satisfaction with interactions, result in the development of trust, which in turn influences customers' dedication to the provider and their willingness to enhance the relationship. Their study, however, does not offer adequate information about the interrelationships, if any, among the variables examined. Furthermore, the level of impact each variable has on trust, dedication, and enhancement could not be clarified.

Verhoef et al.³⁸ examined the effect of relational factors, such as, trust and noneconomic satisfaction, on relationship performance. They did not find a significant effect of trust, and only reported on a small positive effect of noneconomic satisfaction, on contribution margin. Their study, however, examined the influence of relational factors on contribution margin, which may only be indirectly related to cross-buying behaviour. No evidence on the specific relationship between trust and cross-buying intention could be provided.

Bolton et al.¹⁰ examined the effect of satisfaction and payment equity on the length and depth of the relationship. They suggested that customers consider their evaluation of the service quality provided and the price of the service and decide to repurchase, based on their prior intentions or behaviour, reinforced by comparisons with competing offers. The research results showed that perceived fairness, influenced by comparison to competition, is important in determining the length and depth of a relationship. The study, however, only examined the effect of payment equity on the length and the depth of the relationship and not on relationship breadth (cross-buying).

Verhoef et al.²⁸ investigated how satisfaction and payment equity, defined as the perceived fairness of the price, affect cross-buying, taking into account competitors' performance on these factors. According to their findings, the positive effect of satisfaction on cross-buying is increased by relationship length, while satisfaction may have a negative effect for customers in the beginning of their relationships, in that high satisfaction scores in the early phases of the relationship generate high expectations that are difficult to meet. Moreover, payment equity has a negative effect on service additions indicating that low prices of currently held service products do not automatically result in cross-buying. Overall, Verhoef et al.²⁸ examined a number of factors that relate to customers' cross-buying behaviour and provided useful insights. Even so, the analysis performed was a longitudinal one using archival data and measured cross-buying as the difference in the number of services purchased within a specific time period.

Verhoef et al.³⁹ constructed a conceptual framework looking at the effect of trust, satisfaction, and payment equity on cross-buying. According to their framework, the number of different services purchased from a multiservice provider are affected by trust, satisfaction, and payment equity, with the duration of the relationship acting as a moderating variable. They found that payment equity have a significant positive effect on the number of services purchased. Trust, however, was not found to be important with respect to cross-buying. A criticism of this study refers to the fact that Verhoef et al.³⁹ only dealt with the impact of each construct on the number of services purchased, without considering the effect of the interrelationships between the constructs on cross-buying.

Bloemer et al.⁴⁰ examined how customer satisfaction impacts on defection with respect to customers' intention of concentrating more of their banking activities with other banking institutions in the future. According to their research findings, satisfied customers are more likely to concentrate their business with one bank and to respond to cross-selling efforts. Bloemer et al.⁴⁰ confirmed that satisfaction is related to cross-buying intention but their study and their contribution were limited to this.

Ngobo²³ considered the impact of customers' evaluations of service experiences, and customers' perceptions of the provider's capabilities to offer different types of services on cross-buying behaviour. Their results indicated that customers' cross-buying intentions are primarily related to image conflicts about the provider's abilities to deliver different services of equally high quality. Ngobo²³ managed to examine several aspects of cross-buying behaviour, and provided relevant evidence, but he did not try to address the influence of relational constructs, such as trust, on cross-buying intentions.

Overall, synthesising these research propositions and results, there seem to be four key variables that may impact cross-buying intention: satisfaction, payment equity, trust, and image. The majority of the above studies have only implied the relationships between these variables and cross-buying, without providing research evidence for the suggested relationships. Even those few cases where these relationships are actually examined, they include research models that fail to combine all four variables mentioned above. This realisation points to the opportunity to further explore and provide insight into the relationships between particular variables and cross-buying intention.

RESEARCH PROPOSITIONS AND THE RESEARCH MODEL

Along these lines, the main research aim guiding the investigation was to identify some of the key variables that impact simultaneously customers' intention of cross-buying retail financial services and to examine how these variables interrelate. The objectives of this research were:

• — To develop a research model based on previous research studies in the banking industry.
• — To test this model in the Greek retail bank market, to predict customers' cross-buying intention.
• — To examine whether or not the model hypotheses are confirmed, identify possible causes for disconfirmation, and provide implications for further research.

The research model of this study was therefore developed, based on the identified research gaps and combined four important factors of cross-buying: satisfaction, value, image, and trust, as these were identified in extant literature. A number of research propositions were formed:

• — Satisfaction with the bank positively affects customers' cross-buying intention. Satisfaction with the service provider has been the main focus of managers who want to retain their customers.²⁸ Several researchers have found a positive direct or indirect influence of satisfaction with the bank on customers' cross-buying behaviour.^{23, 28 and 40} Customers should be satisfied with the bank and its services in order to consider it for additional purchases.
• — Perceived value positively affects customers' cross-buying intention. Perceived value has been considered in a number of studies^{10, 36 and 39} and has been found to impact loyalty behaviour related to relationship maintenance and relationship depth.¹⁰ Customers who perceive that their bank offers them good value intend to buy additional products from that bank.
• — Perceived image of the bank positively affects customers' cross-buying intention. As financial services are increasingly considered as commodities and the differences between financial services providers diminish,⁴¹ the image of the service provider may play an important role in customers' intention of buying additional financial services (as suggested by Crosby et al.²⁷ Bendapudi and Berry³⁷). Image conflicts about the provider's ability to deliver equally high-quality service in various, different service activities is found to be one of the most important factors impacting cross-buying.²³
• — Trust in the bank positively affects customers' cross-buying intention. Trust has been considered to have a beneficial influence on the development of positive customer attitudes, intentions, and behaviour. More specifically, Bendapudi and Berry³⁷ and Crosby et al.²⁷ have found a positive influence of trust on cross-buying intention.

These four variables are suggested to impact cross-buying but also interrelate with each other, forming a network of relationships between variables. As a result, a complementary set of research propositions are integrated into the research model:

• — Perceived value positively affects customers' satisfaction with the bank
• — Satisfaction with the bank positively affects perceived image of the bank
• — Satisfaction with the bank positively affects trust in the bank.

The above propositions have been generated both from logical reasoning and the qualitative research results, as well as from findings of previous research studies. Particularly, Bolton and Lemon¹¹ Storbacka et al.³⁶ and Ngobo²³ found that perceived value impacts on satisfaction, while Nguyen and LeBlanc⁴² found that satisfaction influences image. Furthermore, Bendapudi and Berry³⁷ and Selnes²⁰ have provided evidence that satisfaction has a positive impact on customers' trust in the bank.

The diagrammatic research model in Figure 1 illustrates and explains the proposed effects of the key factors and the interrelations between these factors. This model serves as the basis for this study; the hypotheses development, the measurement development, the structural equation modelling, and the data analysis are all based on this research model.

Figure 1.

The research model

Full figure and legend (8K)

DESIGN OF THE STUDY

In order to test the research model in the Greek retail bank market, a structured survey questionnaire was designed. The questionnaire was initially developed based on previous research instruments measuring the specific model variables. Moreover, the finalisation of the questionnaire was enabled by means of qualitative research. In-depth personal interviews were carried out with five bank managers, ten bank employees and nine bank customers, so that a holistic view of the research problem could be obtained. The aims of the qualitative study were to gather information from different types of respondents, to offer greater insight into the key variables that impact customers' cross-buying intention, and to contribute to the survey questionnaire design. Participants were asked to share their views and experience on cross-selling efforts and cross-buying behaviour issues. A common set of the most important variables to drive customers' cross-buying intention could be identified. The factors that managers, employees, and customers highlighted as key drivers for cross-buying refer to satisfaction with the bank, trust in the bank, perceived image of the bank, and perceived value, among others.

Quantitative data collection was achieved via self-administration of the questionnaire within two branches of a major bank and street interviewing outside eight branches of five different banks. In the first case, bank customers completed the questionnaire and returned it to a bank employee. In the second case, bank customers were interviewed as they were leaving the bank branch. A nonprobability, quota sample was used for convenience reasons: this was based on age and gender of respondents, in accordance with the proportional distribution in the target population. Quotas were established in order to reduce the high possibility of sampling error, which characterises nonprobability sampling, and to obtain fairly accurate results with respect to the sample representativeness.^{43, 44} The quotas of population elements were based on the 2001 census of the Greek economic energetic population.⁴⁵ 316 customers were surveyed and 311 usable questionnaires were returned.

Several pilot tests and back translation were performed for the development of the questionnaire. Measurement scales were formed according to previous scales and questionnaire pilot tests. The respondents were asked to state their level of agreement with several statements and five-point Likert scales were used to measure multiple items of variables.

For the measurement of cross-buying intention (CB), respondents were asked to focus on their main bank. The indicators were adopted from Tam and Wong⁴⁶ Foster and Cadogan⁴⁷ and Polonsky et al.³⁰ and referred to 'intention of buying more products from the main bank' (cb1), 'choosing the main bank for future purchases' (cb2), 'increasing the volume of business with main bank' (cb3), and 'possibility of purchasing an additional product from main bank' (cb4).

The measurement items used for perceived value (VAL) were adopted from Bolton and Lemon¹¹ and Lewis and Soureli⁴⁸ and referred to 'offering the best deposit interest rates' (val1), 'offering the best loan interest rates' (val2), and 'offering competitive terms' (val3).

Satisfaction (SAT) was measured using items adopted from Ngobo²³ Jamal and Naser⁴⁹ and Tam and Wong⁴⁶ The indicators referred to 'overall satisfaction' (sat1), 'satisfaction from the level of service' (sat2), and 'satisfaction from previous collaboration with the bank' (sat3).

The measurement items used for trust (TR) were adopted from the scales of Verhoef et al.³⁸ Crosby et al.²⁷ and Verhoef et al.³⁹ and referred to 'feeling of dependence on this bank' (tr1), 'bank keeping its promises to customers' (tr2), and 'trust in the bank's integrity and trustworthiness' (tr3).

The measurement scale for image (IM) was formed based on items used by Nguyen and LeBlanc⁵⁰ and Lewis and Soureli.⁴⁸ The indicators that were incorporated referred to 'better image than that of competitors' (im1), 'good impression of the bank' (im2), and 'high opinion of the bank' (im3).

ANALYSIS AND RESULTS

Several methods for data analysis were reviewed, to decide on the most appropriate one for this project. Apart from structural equation modelling, other multivariate methods of analysis can examine only one relationship at a time and use a limited number of variables.^{24, 26} Even those methods that can examine multiple dependent variables, test only a single relation between the dependent and independent variables.⁵¹ As a result, these methods cannot be applied to test sophisticated theories.²⁶ Since one of the study's main objectives was to test how several variables simultaneously affect cross-buying intention, the use of structural equation modelling was necessitated. Structural equation modelling combines path models and confirmatory factor analysis, as it includes both observed variables and latent (unobserved) variables, whether independent or dependent,²⁶ and its main advantage is the ability to estimate and test relations between variables simultaneously.⁵²

Confirmatory factor analysis was performed to examine the scales' reliability and validity. The measurement indicators were found to be reliable (R²>0.35)⁵³ and the calculated scores of Average Variance Extracted (AVE) and Composite Reliability (CR) were above the cut-off points (AVE>0.5,⁵⁴ CR>0.6,²⁴), which provided evidence for construct reliability. All scales showed convergent validity (t-values>1.96),⁵⁵ and exhibited discriminant validity, since the confidence intervals around the correlation estimates between any two factors never included 1.0.²⁷

The research model was specified in a structural model and tested using the Amos 4.0 software.⁵⁶ According to the results, ² statistics did not show a good fit of the model. This is, however, expected, according to Schumacker and Lomax,²⁶ who claim that as the sample size increases over 200, the ² statistic tends to indicate a significant probability level ( p=0.000). Since all the important indicators of the model fit were above the accepted values, this model was considered to be an acceptable one. Moreover, all the research propositions were supported by the significant path coefficients estimated in the model. Specifically, trust in the bank was found to positively affect cross-buying intention (t-value=2.228, p=0.026). Satisfaction positively affects image (t-value=9.377, p=0.000), and trust (t-value=11.696, p=0.000). Image positively affects cross-buying intention (t-value=2.373, p=0.018) and value positively affects satisfaction (t-value=8.491, p=0.000).

There were, however, two research propositions that were not confirmed. These refer to the direct impact of perceived value (t-value=-0.814, p=0.416) and satisfaction (t-value=0.737, p=0.461) on cross-buying intention, as these effects were not statistically significant (p>0.05). Following this finding, the estimates for these two relationships in the structural equation model were fixed to zero for parsimony reasons and the model was re-specified in order to become clearer and less complex. As suggested by Diamantopoulos and Siguaw,⁵³ the parameters, which exhibited insignificant t-values and had signs that did not agree with the theory, were deleted, in that the two arrows linking value and satisfaction to cross-buying intention were removed from the model. The new structural model (shown in Figure 2) was reassessed with respect to its model fit.

Figure 2.

The structural equation model with standardised estimates

Full figure and legend (42K)

The new analysis confirmed the good model fit that was initially assessed. The ² statistics did not show a good fit of the model (as expected according to Schumacker and Lomax²⁶), but all the important indicators of the model fit (with the exception of AGFI) were above the accepted values (see Table 1). Moreover, all the research propositions were supported by the significant path coefficients estimated in the model. For this reason, the new, re-specified, model was considered to be an acceptable one.

Table 1 - Summary of fit indices of the model.

Full table

According to the model results, cross-buying intention is directly influenced by trust (0.549) and favourable image of the bank (0.214). Moreover, it is indirectly influenced by satisfaction (0.621) and perceived value (0.329). Overall, the majority of influence comes from satisfaction, which is the variable with the greater total impact in determining cross-buying intention.

It should be noted though that the above findings are valid and reliable with reference only to the specific model structure. SEM examines how the observed variance–covariance matrix differs from the estimated variance–covariance matrix, which is implied by a particular model specification.⁵⁷ If one observed variable or arrow or latent variable is removed from the model, and the model is reassessed, different findings may be generated. Moreover, there is the risk of generating sample-specific results, which may happen for any of the standard statistical models.⁵²

CONCLUSIONS AND IMPLICATIONS FOR MANAGERS

The overall conclusion of this study is that customers' cross-buying intention is not driven by one single factor, but is formed by a combination of interrelationships between several variables, which should all act simultaneously to be effective. The main contribution of this study relates to the development of a new research model, comprising four key variables: image, trust, satisfaction, and perceived value that interrelate with each other and affect either directly or indirectly the cross-buying intention.

Moreover, this study goes on step further from previous research, as it examined four variables that could fall into two categories: those relating to the past history of the relationship with the bank and customers' previous experience, such as satisfaction, and perceived value and those relating to the expectations or anticipations for the future delivery, which refer to the bank's image and trust in the bank. Following this, there may be some further work that could be done to explore these two different variable categories especially because most cross-selling studies focus on relationships' past history. This research managed to show that customer expectations about anticipated future relationships are also important.

This model fills a research gap that existed concerning strong, organising theoretical frameworks on the key factors leading to cross-buying. No previous study has systematically assessed the relationships between certain variables and cross-buying intention and has provided relevant research evidence. Moreover, many studies have employed research techniques that could not elicit confirmation for the model data fit and hypothesis testing results. The study goes one step further than previous academic research, by combining different variables and examining directly the relationships between these variables and customer cross-buying intention, as well as providing statistical evidence of these relationships and their synergies.

Moreover, the study's practical contribution is versatile, as various managerial directions for successful cross-selling are implied. Strategies for persuading current customers to buy additional products should aim at the development of trust between customers and the bank. Bank managers should be aware of the importance of trust and try to inspire it through constant provision of information, transparency in the bank's processes and charges, delivery of the promises made to customers, reliability in service delivery, and service recovery systems.

The study showed that customers place great importance on the image of their bank and intend to buy additional products from their main bank because they think highly of it. Following this, bank marketers should project an overall positive image of the bank and build a good reputation around the bank's name. Moreover, they should be able to differentiate the bank's image from competition. They should build and preserve an image of integrity and trustworthiness so that customers feel that they can depend on their bank and that their accounts and investments are safe.

Finally, the finding that the impact of customers' satisfaction with their main bank and perceived value on cross-buying intention is not significant indicates that customers would not cross-buy from their main bank simply because so far they are satisfied with it or because the bank offers the most competitive terms. In fact, when trust is developed between the customer and the bank and the bank enjoys a favourable image, the role of satisfaction and value in generating additional sales is secondary and not so important. This, however, does not mean that bank managers should not try to keep their customers delighted or be competitive in terms of their interest rates. Customers may intend to buy more from their bank when they trust it and think highly of it, but only if this is always accompanied by customers' satisfaction with that bank, which in turn is significantly affected by the value that customers perceive that the bank offers. This is why bank managers should offer value for customers' money and, most importantly, make their customers believe that their bank has the most competitive deposit and loan interest rates and the fairest charges, even if it does not. In addition, they should ensure that customers are constantly satisfied and the bank's service meets their expectations.

In conclusion, the current study attempted to explore and examine some key variables influencing customers' intention to buy additional products from the same bank. A research model was developed, tested, and shown to be valid. This model explains part of customers' cross-buying intention and can be used in future studies of other industries, enriched with other variables and compared to other models, so that further statistical support can be found.

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