Subscribe Now Subscribe Today
Research Article
 

An Empirical Research on Conceptualisation of Relational Value



Nasreen Khan, Sharifah Latifah Syed Abdul Kadir and Muhammad Sabbir Rahman
 
Facebook Twitter Digg Reddit Linkedin StumbleUpon E-mail
ABSTRACT

Marketing is regarded as a continuum of exchanges between actors that value must be added in both transaction and relationship aspects. Among the growing studies on customer value creation, relational value is neglected. This study is the first to introduce the conceptualisation of relational value and provide new ideas concerning the dimensions of relational value from the customer perspective. This study also contributes to knowledge on the modelling of multi-dimension cause-effect structure of perceived relational value indirectly related to behavioral intention. Data obtained from 429 survey questionnaires were analyzed using structural equation modelling. The results suggest that confidence and communication are dimensions of relational value. Additionally, this study theorises that relational value impacts on relationship commitment and leads to behavioural intention. Strategic guidelines are provided to managers in designing relational value to stimulate the customer behaviour intention.

Services
Related Articles in ASCI
Search in Google Scholar
View Citation
Report Citation

 
  How to cite this article:

Nasreen Khan, Sharifah Latifah Syed Abdul Kadir and Muhammad Sabbir Rahman, 2012. An Empirical Research on Conceptualisation of Relational Value. Trends in Applied Sciences Research, 7: 829-844.

DOI: 10.3923/tasr.2012.829.844

URL: https://scialert.net/abstract/?doi=tasr.2012.829.844
 
Received: September 11, 2012; Accepted: November 13, 2012; Published: January 01, 2013



INTRODUCTION

Measuring the value of relationships has been highlighted as one of the top priorities by the Marketing Science Institute since 1996. In a very competitive environment where sources are both product-based and process based, competitive advantages are quickly imitated by competitors (Jacobson, 1992). Therefore, a commitment to customer-value innovation is essential in sustaining a competitive advantage (Graf and Maas, 2008). One way to innovate in relation to customer value is to look at the value of the relationship (Komulainen et al., 2004). In the service industry, interactions between two parties are required in order to set the value of services (Kandampully and Duddy, 1999). Therefore, it is necessary to understand the dynamic nature of value creation in the relationship (Eggert et al., 2006). Although, most studies on relationship marketing emphasise customer relationship, the importance of relational value that enhances customer relationships has been neglected (Lindgreen and Wynstra, 2005). In addition, measuring the value of relationships is still in its infancy (Ravald and Gronroos, 1996; Lindgreen and Wynstra, 2005) and no one has yet distinguished the relevant dimensions of relational value (Batt and Purchcase, 2004; Ulaga and Eggert, 2006). Hence, there is great necessity for researchers to consider in-depth how to conceptualise the value of a relationship (Baxter, 2009).

While perceived value has gained attention as a stable construct to predict behavioural intention in the past few years (Hansen et al., 2008), several researchers have confirmed that relationship commitment has a significant role in explaining behavioural intention (Hennig-Thurau et al., 2002; Evanschitzky et al., 2006). While there is need for research on the conceptualisation of relational value, less attention has been given to the role of relational value, which explains relationship commitment and behavioural intention. Therefore, the objectives of this research are, first, to contribute to value creation theory by developing a concept of relational value and its dimensions in the business of customer context and second, to examine the linear relationship between relational value, relationship commitment and behavioural intention.

THEORETICAL BACKGROUND AND HYPOTHESIS DEVELOPMENT

According to Roig et al. (2006), value is an essential element of relationship marketing activities and generating higher value for the customer is the source of competitive advantage in the twenty-first century (Woodruff, 1997; Graf and Maas, 2008). Parallel with the increased research focus on the value of product/service offerings, several researchers have recently attempted to investigate the concept of relational value in the business-to-business context. The reason for the increased interest is that firms have realized that customers make transactions with firms not only because of the value perceived from the goods or service being offered but there may be other factors that make an offer more attractive than others. Many studies have emphasised that the relationship between buyer and supplier is essential when it comes to understanding the concept of value perception. According to relationship theories, the customer creates value together with the producer. The understanding of how a relationship creates value is therefore gaining importance. This is why firms examine all the interactions that create value in any given customer relationship (Gronroos, 1990).

Value in relationship: Relational value is defined as an outcome that results from a collaborative relationship that enhances the competitive abilities of partners (Lapierre, 2000). The primary argument underlying the interest in the concept of relationship is that customers look for the value not only in terms of product/service but also from the relationship that they develop with the seller (Lindgreen and Wynstra, 2005). Based on an extensive review of relationship literature, customer perceived relational value is said to comprise firm’s reputation, conflict handling, communication, interdependence, trust and solidarity.

Reputation: This is defined as the collective assessment of a company’s ability to provide value outcomes to a representative group of stakeholders (Fombrun et al., 2000). Reputation shows how honest the company is and how much they care for their customers (Doney and Cannon, 1997) and, as a result, the customer would trust the company (Kirmani and Rao, 2000). In addition, reputation works as a substantial element of value (Hansen et al., 2008) because it helps to create value (Zabala et al., 2005), sustains the relationship between sellers and buyers (Lopez and Poole, 1998) and also improves loyalty (Roberts and Dowling, 2002).

Conflict handling: Conflict is a blocking behaviour in a working relationship that discourages the parties involved from gaining resources (Anderson and Narus, 1990). Conflict is unavoidable in relational exchanges, particularly in the case of buyer-seller relationships (Skarmeas, 2006). Marketing studies have theorised conflict handling as one of the key underpinnings of relationship marketing (Ndubisi, 2004). It has been proven that conflicts help in earning customer trust and building quality relationships (Ndubisi and Wah, 2005).

Communication: This is defined as an exchange of information between the supplier and the customer to achieve a shared understanding (Duncan and Moriarty, 1998). The marketing literature emphasises the importance of communication through information exchange in both traditional and relational selling (Dwyer et al., 1987). Highly interactive firms spend managerial and financial resources to maintain and develop communication because it is the key to strong relationships and to firm’s performance (Calantone and Schatzel, 2000). Researchers, such as Allen and Wilburn (2002) have provided empirical evidence concerning the important role of communication in supporting customer relationships to obtain customer loyalty.

Interdependence: When both partners, to some degree, depend on one another and the overall amount of resources exchanged, total interdependence exists in a dyad (Kim and Hsieh, 2003). Total interdependence provides important implications for relational exchange (Gundlach and Cadotte, 1994) and, therefore, becomes a critical factor in determining the relationship (Zineldin, 1995). Dash et al. (2006) suggested that perceived interdependence plays an important role in relationship quality.

Trust: This is a fundamental aspect of the relationship climate and it is also one of the factors that differentiate relationships from transactions (Sirdeshmukh et al., 2002). Trust plays a key role in the process of building and maintaining relationships (Morgan and Hunt, 1994). As such, trust has been presented as a central attribute in relationship initiation, formation and maintenance in a variety of exchange contexts (Verhoef et al., 2002). The marketing literature suggests that trust is logically a critical variable in long-term orientation (Ganesan, 1994).

Solidarity: This is the extent to which unity or fellowship arises from common responsibilities and dominates an exchange relationship (Gundlach et al., 1995). It can also be expressed through behaviour, which contributes directly to relationship maintenance and, therefore, represents an asset of tremendous value (Heide and John, 1992). It is reported that when exchange partners express solidarity in a relationship, it improves the long-term orientation (Ivens and Blois, 2004). Consequently, the authors propose the following hypothesis.

H1: customer's perception of reputation, conflict handling, communication, interdependence, trust and solidarity are positively related to the customer perceived relational value
Consequences of relational value: Relationship commitment: This can be described as a partner’s desire to develop a stable relationship and willingness to make short-term sacrifices to maintain it (Jap and Ganesan, 2000). It is also identified as one of the key characteristics of successful relationships (Morgan and Hunt, 1994).

Behavioural intention: Customer loyalty includes both behavioural and attitudinal aspects (Oliver, 1999). The actions of customers, such as word-of-mouth or degree of repeat purchase of a product/service, are said to reflect behavioural loyalty (Chaudhuri and Holbrook, 2001). The attitudinal aspect sees a loyal consumer as someone who has a positive attitude and high degree of commitment (Chaudhuri and Holbrook, 2001). In the absence of measures of actual behaviour, Zeithaml et al. (1996) viewed behavioural intention as an indicator that signals whether customers will remain with or defect from the company. As a result, a number of studies have used behavioural intention to measure customer loyalty (Chaudhuri and Holbrook, 2001). According to Oliver (1999), behavioural intention is defined as an affirmed likelihood to engage in certain behaviour. Behavioural intention can be grouped into two categories (Smith et al., 1999); economic behaviour intentions, such as repeat purchase behaviour (Anderson and Mittal, 2000), willingness to pay more and switching behaviour (Zeithaml et al., 1996) and social behaviour intentions, such as complaint behaviour (Nyer, 1999) and word of mouth communication (Szymanski and Henard, 2001).

The value of the relationship is particularly noteworthy in the service sector because customer perceptions of the relationship value lead customers to commit to the service provider (Claycomb and Martin, 2001). Previous researchers suggested that relational behaviour may even influence relationship quality (Kaufmann, 1987). Therefore, perceived relational value is expected to have a direct effect on relationship commitment.

H2: customer perceived relational value directly influences relationship commitment: Earlier research supports the importance of commitment in relationship marketing (Roos et al., 2006) and, as such, researchers have examined the influence of relationship commitment on various types of customer responses e.g., purchase intentions (Garbarino and Johnson, 1999), service recovery expectations, (Kelly and Davis, 1994) and resistance to change to another provider (Pritchard et al., 1999). The empirical findings from (Morgan and Hunt, 1994) support the view of the relationship between customer commitment and acquiescence, propensity to leave and cooperation. Recent research also proved that commitment is at the core of all strong relationships and that it has a considerable effect on loyalty (Evanschitzky et al., 2006). Therefore, it is expected that relationship commitment influences behavioural intention.

H3: Relationship commitment directly influences behavioural intention
Conceptual framework:
Nowadays in a hypercompetitive environment, product and service attributes are easily imitated by competitors. The only way to survive is to be committed to the customer value. Especially in the service industry, it is difficult to define the value and identify what is of most value to the customers. The first model that introduces the concept of value is the means-end chain model (Gutman, 1982). The model provides an understanding of how consumers perceive the self-relevant outcomes of product use and consumption (Gundlach et al., 1995). Some economists argue that organizations in a competitive environment create value by providing products that are more desired by consumers than those of their competitors (Brynjolfsson and Hitt, 1998). Described value as to fulfil customer needs and it is also an underlying motive for consumer behaviour. Whereas, Gronroos (1996) suggested that value may be relationship related. Indeed, much of the literature also proved that a relationship between the buyer and supplier is essential when it comes to understanding the concept of value perception. In fact, Kandampully and Duddy (1999) stated that the customer is the one who creates the value together with the producer and it is the relationship that sets the value of the service. Hence, the relationship itself might have a major effect on the total value perceived.

Attitude is derived from an individual’s response to a stimulus and is also useful in the prediction of subsequent behaviour (Fiske and Taylor, 1991). Ajzen (2001) pointed out the importance of attitude in explaining individual evaluation to form behavioural intention.

Image for - An Empirical Research on Conceptualisation of Relational Value
Fig. 1: A conceptual framework

Particularly, Palmatier et al. (2007) focused on relationship commitment as the attitude component that plays a role between evaluative variables and behaviour outcomes. Indeed, Pura (2005) empirically tested and confirmed that relationship commitment plays an important role as an attitude between value and behavioural intention. Figure 1 shows a hypothesised model of a set of constructs and explains the relationship among them. The six constructs on the left of the model are the proposed dimensions of relational value.

Based on Ajzen (2001) theory of reason and action, the model is conceptualised as the individual’s affective evaluation of perceived relational value that impact on attitude, i.e., relationship commitment, which then leads to behavioural intention. The model illustrated in Fig. 1 provides a conceptual framework for the research.

METHODS

Based on extensive literature reviews, the constructs in the hypothesised model are developed. Interviews with three managers, three academic experts and ten customers were conducted in order to check the validity of the constructs. During the pre-testing stage, there were a few pre-judgments about which indicators should be included in order to capture the dimensions of perceived relational value. Later, pilot testing was conducted on 50 random customers by asking them to complete a draft questionnaire in order to detect any problems in the questions. Their comments on the content and structure of the questionnaire were considered before the questionnaire was finalized. The data from the pilot study was analysed to test for reliability and the results show a high Cronbach’s alpha score, above 0.90, for all the constructs.

Measurement instrument development: The literature review provided basic research support to develop the conceptual framework and major research constructs. All the scales used were adapted from previous studies and consist of reflective measures (Diamantopoulos and Winklhofer, 2001). Statements were adapted to suit the nature of the study. Since sources of measurement scales related to relationship commitment (Fullerton, 2005; Hennig-Thurau et al., 2002) and behavioural intention (Zeithaml et al., 1996) are widely available; a set of existing measures was modified and adopted.

Regarding the measurement scales of the perceived relational value dimensions, the indicators of constructs were adapted from an extensive review of the relationship literature. For the first dimension of perceived relational value, i.e., conflict handling, it was measured with three items that were adapted from Dwyer et al. (1987) and Ndubisi and Wah (2005). The second dimension of trust with four items was adapted from Moorman et al. (1993). The third dimension of solidarity with four items was adapted from Lapierre (2000) and the fourth dimension of reputation with three items was adapted from Flavian et al. (2004). The fifth dimension of communication with four items was adapted from Morgan and Hunt (1994) and Ball et al. (2004) and the last dimension of interdependence with four items was adapted from Jap and Ganesan (2000). All the measurement items are coded (Appendix 1).

Sample and data collection: The targeted population of this study is individuals who are the bank customers in Malaysia. The reason for selecting bank customers as the sample of study is that Malaysia’s financial system is a key contributor to the economic growth (Bank Negara Malaysia, 2008) and evidence suggests that the financial services sector has not created as much value as it should have. In addition, there is an urgent need for banks to pay closer attention to building profitable, long-term customer relationships (Omarini, 2011). Based on the previous researchers’ recommendations, this research decided to target a total of 600 respondents from the banking industry. Four hundred and seventy two (472) responses were received achieving a response rate of 78%; 429 questionnaires were completely filled out and useable for analysis while 43 questionnaires were returned incomplete. According to the previous studies (for instance: Matzler et al., 2006; Molina et al., 2007; Roig et al., 2009), the convenience sampling method is widely used in banking research. In this type of sampling method, subjects are taken wherever and whenever they are handy (De Veaux et al., 2004). Given the exploratory nature of this study, convenience sampling is suitable for this research (Zikmund, 2003).

Based on the suggestions of previous researchers (Al-Hawari and Tony, 2006; Molina et al., 2007), the best sources of information about individual behaviour are individual revelations about themselves. In addition, this approach focuses on the people being studied and provides a better explanation from the individuals (Veal, 2005). Hence, this research used self-administered questionnaire to collect the data.

Sampling adequacy: In order to determine and examine sampling adequacy, this study utilized three approaches, the empirical evidence drawn from the previous research, the guidelines of research methods and the statistical findings. This study used two measures of statistical techniques provided by factor analysis: Kaiser-Meyer-Olkin (KMO) as well as Bartlett’s test of sphericity to test the sampling adequacy. According to Sheridan and Lyndall (2003) and Hair et al. (2006), the KMO must be above 0.5. This study meets the requirement of the KMO designated levels for values of sampling adequacy. According to George and Mallery (2003), Bartlett’s test measures the multivariate normality of the data set distribution and suggests that if there are correlations in the data set, it is appropriate for factor analysis. This study met the criteria and, therefore, it was concluded that the data are appropriate for the analysis.

RESULTS

Exploratory Factor Analysis (EFA) is used as a first step to identify and validate the factor groupings reflecting the underlying theoretical constructs. To aid interpretation, Varimax rotation was applied to simplify the interpretation of factors (Tabachnick and Fidell, 2001) and confirmatory analysis was used for the development and evaluation of scales. Confirmatory factor analysis techniques assist in the confirmation and validation of the uni-dimensionality of constructs. Subsequently, a measurement model comprising all the constructs and their indicators is specified in the Amos structural equation modelling and then re-specified to obtain a good fit by removing the indicators.

Descriptive analysis: This section provides a descriptive analysis and discusses the respondent’s profiles based on the demographic characteristics. There were two main reasons for analyzing the demographic characteristics of the respondents of the research. First, a clear profile of the characteristics of the respondents had to be established and second, the representativeness of the samples of the population being studied had to be assessed. SPSS 16.0 was used for descriptive analysis of the demographic characteristics of the 429 respondents. Frequency tests were performed to determine demographic characteristics of the sample. Among the analysed samples (N = 429), 55% of the respondents were female, 52% were married, 48% had at bachelor degree and 47% fell in the age group between 18 to 34 years. In terms of income group, 51% of the respondents fell in the group RM 3000 and above.

Exploratory factor analysis: The proposed relational value construct consists of six dimensions (conflict handling, trust, solidarity, reputation, communication, interdependence) which are measured by 22 items, as shown in Appendix. Since, the concept of perceived relational value is a totally new research area, there are no established scales developed to measure them. As such, prior to performing the Principal of Component Analysis (PCA), the suitability of data for factor analysis was assessed. An inspection of the correlation matrix of relational value which consists of six dimensions, indicates that (a) a number of correlations exceed 0.30, (b) the Bartlett’s test of sphericity (χ2 = 5456.081, p<0.000) is significant and (c) the KMO = 0.949, which is adequate and, therefore, factor analysis is appropriate. Later, six dimensions were factorised and the solution was rotated using the orthogonal method with the Varimax rotational approach, as suggested by Hair et al. (2006).

The results from exploratory factor analysis only indicate two strong factors (Table 1). The first factor extracted, measured by six items, reflects the extent to which customers have confidence in the way the firm is solving the problems or carrying out the transactions and, thus, it is termed as Relational confidence (RCOF). The second factor, measured by four items, focuses on the extent to which the firm is able to communicate through personal service or constantly informs and, thus, it is termed as Relational communication (RCOM).

Confirmatory factor analysis (CFA): Following Gerbing and Anderson (1988), the measurement model (relationships between observed items and latent constructs) was analyzed before the structural model (relationships between latent constructs). Using the CFA allows a more rigorous interpretation of uni-dimensionality as well as the acceptability of the scale in terms of composite reliability and convergent validity.

The fit of the CFA model is assessed based on a number of fit indices, including chi-square, relative chi-square, goodness-of-fit (GFI), Root Mean Square Error of Approximation (RMSEA), Normed Fit Index (NFI), Comparative Fit Index (CFI), Relative Fit Index (RFI), adjusted goodness of fit index (AGFI) and Parsimony Normed Fit Index (PNFI). The results from the measurement model met the criteria set by Hair et al. (2006) and, therefore, indicate a good-fit model. The goodness-of-fit statistics for the measurement model is shown in Table 2.

In order to establish construct validity, researchers need to examine the correlations with other measures so that convergent validity can be achieved (Churchill, 1979). Fornell and Larcker (1981) suggested that convergent validity is achieved if its composite reliability is larger than 0.50. In addition, convergent validity is also examined using Average Variance Extracted (AVE). According to Fornell and Larcker (1981), average variance extracted (AVE) must exceed the recommended level of 0.50 for all constructs. As shown in Table 3, all the constructs in this study meet the criteria and, therefore, it can be concluded that, the relational value comprises confidence and communication which are the dimensions of perceived relational value.

Table 1: Perceived Relational value (RV) Two-factor Varimax Rotated Results
Image for - An Empirical Research on Conceptualisation of Relational Value
COF: Conflict, TR: Trust, COM: Communication RCOF: Relational Confidence, RCOM: Relational communication

Table 2: Goodness-of-fit statistics
Image for - An Empirical Research on Conceptualisation of Relational Value

Table 3: Reliability and validity
Image for - An Empirical Research on Conceptualisation of Relational Value

Image for - An Empirical Research on Conceptualisation of Relational Value
Fig. 2: Structural model of perceived relational value to behavioural intention

The results of the study suggest that bank customers perceive the multidimensional nature of relational value and they assess the relational value in terms of confidence and communication.

Structural model: Formulating the structural model is derived from the review of extensive literature and well established theories. Figure 2 displays a total of 23 indicators that measure the original structural model.

There are 5 variables in the model: relational confidence (RCOF) and Relational communication (RCOM), Perceived Relational Value (PRV), Relationship Commitment (RC) and Behavioural Intention (BI). The model portrays that independent factors are hypothesised as exerting an influence on the dependent factors. To test the relationships between all the constructs and measures, the structural equation modelling technique with maximum likelihood estimation in AMOS 16.0 was used.

The results displayed in Table 2 suggest an acceptable average fit of the original structural model with the χ2 = 785.94, χ2/df = 2.99, RMSEA = 0.076, CFI = 0.92 and GFI = 0.86. Although, the model is marginally satisfactory, as suggested by Hair et al. (2006), a review of the Modification Indices (MI) reveals some evidence of misfit in the model. It is noted that the maximum MI value is associated with the regression path flowing from BI5-BI6. Both items measure the behavioural intention (BI). The value of 69.25 indicates that if these parameters were to be freely estimated in a subsequent model, the overall χ2 value would drop by at least this amount. Item BI5 is “encourage friends and relatives to use this bank” and BI6 is “recommend about this bank to close friends/relatives” Clearly, these two items seem to be stating the same idea although the wording has been slightly modified. With a Modification Index (MI) of 69.25, it is clear that the error covariance between items BI5 and BI6 represents a minor model misspecification.

The original structural model is re-specified by linking the two items of BI5 and BI6, as suggested by Byrne (2001). After the model was re-specified, the overall model fit improved with χ2 = 677.80 and the GFI increased slightly to 0.88, CFI to 0.93 and RMSEA to 0.069. This model is subsequently labelled as the modified structural model I. Comparing with the original structural model, the modified structural model I appears to be better on the basis of the GFI, CFI and RMSEA values and the model difference is statistically significant (Δχ2 = 108.14).

In reviewing the misspecification statistics, the largest MI value of 40.15 is still associated with a path flowing from (RC1_RC2). Thus, it is evident that the modified structural model I could be further improved. It is found that there is a large error covariance between two items, i.e., RC1 and RC2 both of which measure relationship commitment (RC). RC1 measures “feel emotionally attached to the bank” and RC2 measures “a great deal of personal meaning”. Obviously, these two items appear to be stating the same idea. Thus, the modified structural model I is re-specified by linking between two items, which is RC1 to RC2, as suggested by Bryne (2001). After the model was re-specified, the overall model fit improved with χ2 = 621.79 with GFI = 0.90, CFI = 0.95 and RMSEA = 0.060. The model is labelled as modified structural model II.

The χ2 difference between the modified structural model I and modified structural model II is statistically significant (Δχ2 = 56.01). There are only slight changes in the GFI (0.90), CFI (0.95) with a slight improvement in RMSEA (0.060), thereby indicating that the modified structural model II represents the best fit to the data. As expected, there are no outstanding values that suggest model misfit. Taking each of these factors into account, no further changes were needed to the model. The modified structural model II is named as the structural model of perceived relational value to behavioural intention.

Path analysis: Table 4 shows the model paths are significant at p<0.001. A squared multiple correlation of 0.65 for relationship commitment and 0.60 for behavioural intention indicate that 65% of the variance of relationship commitment is explained by perceived relational value and 60% of variance of behavioural intention is explained by relationship commitment and perceived relational value. As indicated by the significance level, there is positive influence of perceived relational value to relational confidence (β = 0.811) and relational communication (β = 0.946). In the same way, there is a positive path loading from perceived relational value to relationship commitment (β = 0.803) and relational commitment to behavioural intention (β = 0.776).

The results of this study indicate that the relational value of confidence and communication influence the relationship commitment. This finding reflects past findings, which state that customers who perceived the relationship benefit commit to the organization (Kaufmann, 1987). Hence, the findings of this study draw attention to the role of relational value in explaining customer relationship commitment. Finally, this study also confirmed that relationship commitment directly influences behavioural intention. Therefore, this study aligns with previous findings which state that commitment is at the core of all strong relationships and that it has a considerable effect on loyalty (Evanschitzky et al., 2006).

Table 4: Path coefficient for structural model
Image for - An Empirical Research on Conceptualisation of Relational Value
Significant level, *p<0.05, **p<0.01 and *** p<0.001

THEORETICAL AND MANAGERIAL IMPLICATIONS

The present study contributes to the literature in several ways. This study is the first to introduce the concept of relational value in business to the consumer service context because the concept is still in the exploratory stage even in the business-to-business context (Baxter, 2009). Based on the author’s knowledge, there is no empirical study that provides evidence for the perceived relational value in customer relationship marketing research. The exploratory and confirmatory analysis indicates that the 10-item scale and its two dimensions have stable psychometric properties. The scale describes that consumers evaluate the relational value in terms of confidence and communication. Thus, this study contributes to relationship marketing theories by identifying two dimensions of customers perceived relational value-relational confidence and relational communication.

Another major implication of this study concerns the importance of the perceived relational value in assessing its direct influence on relationship commitment and then leads to behavioural intention. To the author’s knowledge, this is one of very few studies that investigate the linear relationship between perceived relational value, relationship commitment and behavioural intention. This study contributes to customer relationship management literature and finds that perceived relational value which consists of confidence and communications, influence relationship commitment and then lead to behavioural intention.

The research also provides outcomes that will be useful for managers. This study provides the directions for bank service providers who wish to create and deliver relational value. Thus, to be able to build a relationship commitment with the customer, banks must design loyalty programmes that emphasize on building employees’ confidence and continuous communication with the customers. Since evaluation of relational value is based on consumer perception, banks should promote expert and trustworthy employees that enhance the customers’ perceptions of relational value. This study provides empirical evidence for managers that once customers perceive the value in the relationship, they will be emotionally committed to a relationship. Furthermore, since this study found that relationship commitment directly influences customer behavioural intention, banks must develop relationship management programmes that build recognition and shared value-based commitment and emotional support that are likely to be effective at building customer behavioural intention. Service providers may also build customer commitment through responsive communication with customers and show confidence in dealing with them.

LIMITATIONS AND FUTURE RESEARCH

Although, this study reports significant implications concerning the development of multidimensional measures of relational value and its influence on relationship commitment, which then leads to behavioural intention, the validity of an instrument cannot be firmly established on the basis of a single study. In addition, this study is conducted using data from bank customers in Malaysia and so its generalization beyond this situation may be limited. Therefore, it would be interesting to see how the results vary across industries and across countries in future research.

Furthermore, this study does not look into the importance of customers’ demographic characteristics, such as age, income, gender and culture, in explaining the customer behaviour. Despite the recent growing interest in the demographic variables concerning attitude and behavioural intention, the relationships between demographic factors and value dimensions have not yet been investigated. Hence, future research should look into the role of demographic variables in explaining the customers’ perceived relational value dimensions of attitude and behaviour. This suggests that service providers create effective market segmentation and targeting strategies in identifying customer perceived value, forming their attitude and leading to behavioural intention.

APPENDIX 1

Measurement items of relationship commitment
Image for - An Empirical Research on Conceptualisation of Relational Value

Measurement items of behavioural intention
Image for - An Empirical Research on Conceptualisation of Relational Value

Initial factors and measurement items of relational value
Image for - An Empirical Research on Conceptualisation of Relational Value

REFERENCES

1:  Ajzen, I., 2001. Nature and operation of attitudes. Ann. Rev. Psychol., 52: 27-58.
Direct Link  |  

2:  Al-Hawari, M. and T. Ward, 2006. The effect of automated service quality on australian banks financial performance and the mediating role of customer satisfaction. Market. Int. Plann., 24: 127-147.
CrossRef  |  Direct Link  |  

3:  Allen, D.R. and M. Wilburn, 2002. Linking Customer and Employee Satisfaction to the Bottom Line: A Comprehensive Guide to Establishing the Impact of Customer and Employee Satisfaction on Critical Business Outcomes. ASQ Quality Press, Milwaukee, USA., ISBN-13: 9780873895019, Pages: 238

4:  Anderson, E.W. and V. Mittal, 2000. Strengthening the satisfaction-profit Chain. J. Service Res., 3: 107-120.
CrossRef  |  Direct Link  |  

5:  Anderson, J.C. and J.A. Narus, 1990. A model of distributor firm and manufacturer firm working partnerships. J. Market., 54: 42-58.
CrossRef  |  Direct Link  |  

6:  Ball, D., P.S. Coelho and A. Machas, 2004. The role of communication and trust in explaining customer loyalty: An extension to the ECSI model. Eur. J. Market., 38: 1272-1293.
CrossRef  |  

7:  Bank Negara Malaysia, 2008. Annual Report 2008. Bank Negara Malaysia, Kuala Lumpur

8:  Batt, P.J. and S. Purchase, 2004. Managing collaboration within networks and relationships. Ind. Market. Manage., 33: 169-174.
CrossRef  |  

9:  Baxter, R., 2009. Reflective and formative metrics of relationship value: A commentary essay. J. Bus. Res., 62: 1370-1377.
Direct Link  |  

10:  Brynjolfsson, E. and L.M. Hitt, 1998. Beyond the productivity paradox: Computers are the catalyst for bigger changes. ACM Commun., 41: 49-55.
Direct Link  |  

11:  Byrne, B.M., 2001. Structural Equation Modeling with AMOS: Basic Concepts, Application and Programming. 1st Edn., Lawrence Erlbaum Associates, Mahwah, New Jersey, USA., ISBN-13: 9780805841046, Pages: 352

12:  Calantone, R.J. and K.E. Schatzel, 2000. Strategic foretelling: Communication-based antecedents of a firm's propensity to preannounce. J. Market., 64: 17-31.
Direct Link  |  

13:  Chaudhuri, A. and M.B. Holbrook, 2001. The chain of effects from brand trust and brand affect to brand performance: The role of brand loyalty. J. Market., 65: 81-93.
CrossRef  |  Direct Link  |  

14:  Churchill, Jr. G.A., 1979. A paradigm for developing better measures of marketing constructs. J. Market. Res., 16: 64-73.
Direct Link  |  

15:  Claycomb, C. and C.L. Martin, 2001. Building customer relationships: An inventory of service providers objectives and practices. Market. Intell. Plan., 19: 385-399.
CrossRef  |  

16:  Sheridan, J.C. and G.S. Lyndall, 2003. SPSS Analysis without Anguish. Version 11, John Wiley and Sons, Australia

17:  George, D. and P. Mallery, 2003. SPSS for Windows Step by Steps: A Simple Guide and Reference. 4th Edn., Allyn and Bacon. Boston, pages: 231

18:  Dash, S., E. Bruning and K.K. Guin, 2006. The moderating effect of power distance on perceived interdependence and relationship quality in commercial banking: A cross-cultural comparison. Int. J. Bank Market., 24: 307-326.
CrossRef  |  

19:  De Veaux, R.D., P.F. Vellman and D.E. Block, 2004. Introductory Statistics. Pearson Addison Wesley, Boston, MA., USA., Pages: 648

20:  Diamantopoulos, A. and H. Winklhofer, 2001. Index construction with formative indicators: An alternative to scale development. J. Marketing Res., 38: 269-277.
CrossRef  |  Direct Link  |  

21:  Doney, P.M. and J.P. Cannon, 1997. An examination of the nature of trust in buyer-seller relationships. J. Market., 61: 35-51.
CrossRef  |  Direct Link  |  

22:  Duncan, T. and S.E. Moriarty, 1998. A communication-based marketing model for managing relationships. J. Market., 56: 1-13.
Direct Link  |  

23:  Dwyer, F.R., P.H. Schurr and S. Oh, 1987. Developing buyer-seller relationships. J. Market., 51: 11-27.
CrossRef  |  Direct Link  |  

24:  Eggert, A., W. Ulaga and F. Schultz, 2006. Value creation in the relationship life cycle: A quasi-longitudinal analysis. Ind. Market. Manage., 35: 20-27.
CrossRef  |  

25:  Evanschitzky, H., G.R. Iyer, H. Plassmann, J. Niessing and H. Meffert, 2006. The relative strength of affective commitment in securing loyalty in service relationships. J. Bus. Res., 59: 1207-1213.
CrossRef  |  

26:  Fiske, S.T. and S.E. Taylor, 1991. Social Cognition. 2nd Edn., McGraw-Hill, New York

27:  Flavian, C., E. Torres and M. Guinaliu, 2004. Corporate image measurement: A further problem for the tangibilization of Internet banking services. Int. J. Bank Market., 22: 366-384.
CrossRef  |  

28:  Fombrun, C., N.A. Gardberg and J.M. Sever, 2000. The reputation quotient: A multi-stakeholder measure of corporate reputation. J. Brand Manage., 7: 241-255.

29:  Fornell, C. and D.F. Larcker, 1981. Evaluating structural equation models with unobservable variables and measurement error. J. Market. Res., 18: 39-50.
CrossRef  |  Direct Link  |  

30:  Fullerton, G., 2005. How commitment both enables and undermines marketing relationships. Eur. J. Market., 39: 1372-1388.
CrossRef  |  Direct Link  |  

31:  Ganesan, S., 1994. Determinants of long-term orientation in buyer-seller relationships. J. Marketing, 58: 1-19.
Direct Link  |  

32:  Garbarino, E. and M.S. Johnson, 1999. The different roles of satisfaction, trust and commitment in customer relationships. J. Market., 63: 70-87.
CrossRef  |  Direct Link  |  

33:  Gerbing, D.W. and J.C. Anderson, 1988. An updated paradigm for scale development incorporating unidimensionality and its assessment. J. Market. Res., 25: 186-192.
CrossRef  |  Direct Link  |  

34:  Graf, A. and P. Maas, 2008. Customer value from a customer perspective: A comprehensive review. Business Econ., 58: 1-20.
CrossRef  |  

35:  Gronroos, C., 1996. Relationship marketing logic. Asia-Aust. Market. J., 4: 7-18.
CrossRef  |  

36:  Gronroos, C., 1990. Service Management and Marketing: Managing the Moments of Truth in Service Competition. Lexington Books, Lexington, MA., USA., ISBN: 9780669200355, Pages: 298

37:  Gundlach, G.T., R.S. Achrol and J.T. Mentzer, 1995. The structure of commitment in exchange. J. Market., 59: 78-92.
CrossRef  |  Direct Link  |  

38:  Gutman, J., 1982. A means-end chain model based on consumer categorization processes. J. Market., 46: 60-72.
CrossRef  |  Direct Link  |  

39:  Hair, J.F., W.C. Black, B.J. Babin, R.E. Anderson and R.L. Tatham, 2006. Multivariate Data Analysis. 6th Edn., Prentice-Hall Inc., New Jersey, USA., ISBN-13: 9780130329295, Pages: 899

40:  Hansen, H., B.M. Samuelsen and P.R. Silseth, 2008. Customer perceived value in B-t-B service relationships: Investigating the importance of corporate reputation. Ind. Market. Manage., 37: 206-217.
CrossRef  |  Direct Link  |  

41:  Heide, J.B. and G. John, 1992. Do norms matter in marketing relationships? J. Market., 56: 32-44.
Direct Link  |  

42:  Ivens, B.S. and K.J. Blois, 2004. Relational exchange norms in marketing: A critical review of Macneil's contribution. Market.Theory, 4: 239-263.
CrossRef  |  

43:  Jacobson, R., 1992. The Austrian school of strategy. Acad. Manage. Rev., 17: 782-807.
Direct Link  |  

44:  Jap, S.D. and S. Ganesan, 2000. Control mechanisms and the relationship life cycle: Implications for safeguarding specific investments and developing commitment. J. Market. Res., 37: 227-245.
CrossRef  |  

45:  Kandampully, J. and R. Duddy, 1999. Relationship marketing: A concept beyond the primary relationship. Market. Intell. Plan., 17: 315-323.
CrossRef  |  

46:  Kaufmann, P.J., 1987. Commercial exchange relationships and the negotiator's dilemma. Negotiation J., 3: 73-80.
CrossRef  |  

47:  Kelly, S.W. and M.A. Davis, 1994. Antecedents to customer expectations for service recovery. J. Acad. Market. Sci., 22: 52-61.
CrossRef  |  

48:  Kirmani, A. and A.R. Rao, 2000. No pain, no gain: A critical review of the literature on signaling unobservable product quality. J. Market., 64: 66-79.
CrossRef  |  

49:  Komulainen, H., T. Mainela, J. Tahtinen and P. Ulkuniemi, 2004. Exploring customer perceived value in a technology intensive service innovation. Proceedings of the 20th IMP Conference, September 2-4, 2004, Copenhagen, Denmark, pp: 1-27
Direct Link  |  

50:  Lapierre, J., 2000. Customer-perceived value in industrial contexts. J. Bus. Indus. Market., 15: 122-145.
CrossRef  |  Direct Link  |  

51:  Lindgreen, A. and F. Wynstra, 2005. Value in business markets: What do we know? Where are we going? Ind. Market. Manage., 34: 732-748.
CrossRef  |  Direct Link  |  

52:  Lopez, R.C. and N. Poole, 1998. Quality assurance in the maritime port logistic chain. Supply Chain Manage., 3: 33-44.
CrossRef  |  

53:  Matzler, K., S. Bidmon and S. Grabner-Krauter, 2006. Individual determinants of brand affect: The role of the personality traits of extraversion and openness to experience. J. Prod. Brand Manage., 15: 427-434.
Direct Link  |  

54:  Molina, A., D. Martin-Consuegra and A. Esteban, 2007. Relational benefits and customer satisfaction in retail banking. Int. J. Bank Market., 25: 253-271.
CrossRef  |  

55:  Moorman, C., R. Deshpande and G. Zaltman, 1993. Factors affecting trust in market research relationships. J. Market., 57: 81-101.
Direct Link  |  

56:  Morgan, R.M. and S.D. Hunt, 1994. The commitment-trust theory of relationship marketing. J. Market., 58: 20-38.
CrossRef  |  Direct Link  |  

57:  Ndubisi, N.O., 2004. Understanding the salience of cultural dimensions on relationship marketing, it's underpinnings and aftermaths. Cross Cult. Manage., 11: 70-89.
CrossRef  |  

58:  Ndubisi, N.O. and C.K. Wah, 2005. Factorial and discriminant analyses of the underpinnings of relationship marketing and customer satisfaction. Int. J. Bank Market., 23: 542-557.
CrossRef  |  

59:  Nyer, P.U., 1999. Cathartic complaining as a means of reducing consumer dissatisfaction. J. Consum. Satisfaction Dissatisfaction Complaining Behav., 12: 15-25.
Direct Link  |  

60:  Oliver, R.L., 1999. Value as Excellence in the Consumption Experience. In: Consumer Value: A Framework for Analysis and Research, Holbrook, M.B. (Ed.). Routledge, London, UK., pp: 43-62

61:  Omarini, A., 2011. Retail banking: The challenge of getting customer intimate. J. Banks Bank Syst., 6: 78-89.

62:  Palmatier, R.W., R.P. Dant and D. Grewal, 2007. A comparative longitudinal analysis of theoretical perspectives of interorganizational relationship performance. J. Market., 71: 172-194.
Direct Link  |  

63:  Pritchard, M.P., M.E. Havitz and D.R. Howard, 1999. Analysing the commitment-loyalty link in service contexts. J. Acad. Market. Sci., 27: 333-348.
CrossRef  |  

64:  Pura, M., 2005. Linking perceived value and loyalty in location-based mobile services. Managing Serv. Qual., 15: 509-538.
CrossRef  |  Direct Link  |  

65:  Ravald, A. and C. Gronroos, 1996. The value concept and relationship marketing. Eur. J. Market., 30: 19-30.
CrossRef  |  Direct Link  |  

66:  Roberts, P.W. and G.R. Dowling, 2002. Corporate reputation and sustained superior financial performance. Strat. Manage. J., 23: 1077-1093.
CrossRef  |  

67:  Roig, J.C.F., J.S. Garcia, M.A.M. Tena and J.L. Monzonis, 2006. Customer perceived value in banking services. Int. J. Bank Market., 24: 266-283.
CrossRef  |  Direct Link  |  

68:  Roig, J.C.F., J.S. Garcia, M. Angel and M. Tena, 2009. Perceived value and customer loyalty in financial services. J. Service Ind., 29: 775-789.
CrossRef  |  

69:  Roos, I., A. Gustafsson and B. Edvardsson, 2006. Defining relationship quality for customer-driven business development: A housing-mortgage company case. Int. J. Serv. Ind. Manage., 17: 207-223.
CrossRef  |  

70:  Sirdeshmukh, D., J. Singh and B. Sabol, 2002. Consumer trust, value and loyalty in relational exchanges. J. Market., 66: 15-37.
Direct Link  |  

71:  Skarmeas, D., 2006. The role of functional conflict in international buyer-seller relationships: Implications for industrial exporters. Ind. Market. Manage., 35: 567-575.

72:  Smith, A.K., R.N. Bolton and J. Wagner, 1999. A model of customer satisfaction with service encounters involving failure and recovery. J. Market. Res., 36: 356-372.
Direct Link  |  

73:  Tabachnick, B.G. and L.S. Fidell, 2001. Using Multivariate Statistics. 4th Edn., Allyn and Bacon, Boston, MA., USA

74:  Ulaga, W. and A. Eggert, 2006. Relationship value and relationship quality: Broadening the nomological network of business-to-business relationships. Eur. J. Market., 40: 311-327.
CrossRef  |  

75:  Veal, A.J., 2005. Business Research Method: A Managerial Approach. 2nd Edn., Frenchs Forest, Pearson Addison Wesley, London

76:  Verhoef, P.C., P.H. Franses and J.C. Hoekstra, 2002. The effect of relational constructs on customer referrals and number of services purchased from a multiservice provider: Does age of relationship matter? J. Acad. Market. Sci., 30: 202-216.
CrossRef  |  Direct Link  |  

77:  Woodruff, R.B., 1997. Customer value: The next source for competitive advantage. J. Acad. Market. Sci., 25: 139-153.
CrossRef  |  Direct Link  |  

78:  Zabala, I., G. Panadero, L.M. Gallardo, C.M. Amate, M. Saanchez-Galindo, I. Tena and I. Villalba, 2005. Corporate reputation in professional services firms: Reputation management based on intellectual capital management. Corporate Reputat. Rev., 8: 59-71.
CrossRef  |  

79:  Zeithaml, V.A., L.L. Berry and A. Parasuraman, 1996. The behavioral consequences of service quality. J. Market., 60: 31-46.
CrossRef  |  Direct Link  |  

80:  Zikmund, W., 2003. Exploring Marketing Research. 8th Edn., Thomson/South-Western, Ohio, USA., ISBN-13: 9780324181487, Pages: 744

81:  Zineldin, M., 1995. Bank-company interactions and relationships: Some empirical evidence. Int. J. Bank Market., 13: 30-40.
CrossRef  |  

82:  Szymanski, D.M. and D.H. Henrad 2001. Customer satisfaction: A meta analysis of the empirical evidence J. Acad. Market. Sci., 29: 16-35.
CrossRef  |  

83:  Hennig-Thurau, T., K.P. Gwinner and D.D. Gremier, 2002. Understanding relationship marketing outcomes: An integration of relational benefits and relationship quality. J. Serv. Res., 4: 230-247.
CrossRef  |  Direct Link  |  

84:  Kim, S.K. and P.H. Hsieh, 2003. Interdependence and its consequences in distributor-supplier relationships: A distributor perspective through response surface approach. J. Marketing Res., 40: 101-112.
Direct Link  |  

85:  Gundlach, G.T. and E.R. Cadotte, 1994. Exchange interdependence and interfirm interaction: Research in a simulated channel setting. J. Marketing Res., 31: 516-532.
Direct Link  |  

©  2021 Science Alert. All Rights Reserved