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Banks’ Lending Relationship Quality Index (LRQI) for the Small and Medium-Sized Enterprises: A Review

Hypotheses and theory

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International Journal of Innovation and Economic Development
Volume 4, Issue 3, August 2018, Pages 32-40

Banks’ Lending Relationship Quality Index (LRQI) for the Small and Medium-Sized Enterprises: A Review

DOI: 10.18775/ijied.1849-7551-7020.2015.43.2004
URL: http://dx.doi.org/10.18775/ijied.1849-7551-7020.2015.43.2004

Tury Retap, Firdaus Abdullah, Jamil Hamali

Malayan Banking Bhd, SME Business Centre, Jalan Kampong Nyabor, Sibu, Malaysia
2 3 Faculty of Business Management, Universiti Teknologi MARA, Jalan Meranek, Malaysia

Abstract: Stiff competition in the service industry like banking sector has forced banks to search for the best approach to create, attract and retain a segment of satisfied customers. Relationship marketing is a comprehensive strategy used by many service providers to maintain an on-going long-term relationship with their existing customers. A proper implementation of relationship marketing activities is evident from good relationship quality built between the customer and the service provider. Due to the above needs, development of a new measuring instrument (Lending Relationship Quality Index (LRQI) to assess the quality of lending relationship between the banks and their SM E borrowings’ customers, a nationwide survey is proposed to identify factors presumed to influence the quality of lending relationship from SME borrowings’ customers perspective A sample size of 2,000 will be drawn from the SME customers having lending relationship with domestic commercial banks. The sampling procedures to be used for this study will be Convenient Sampling. The items in the questionnaire will be measured on a five-point Likert – type scale. Previous researches had focused on assessing relationship quality between the banks and their customers but have neglected to determine the quality of relationship in the context of lending between the banks and their SME borrowings’ customers. The new measuring instrument will be empirically tested for multi-dimensionality, reliability and validity by using both exploratory and confirmatory factor analysis. The findings from this study will add value to the existing literatures on relationship quality by linking the proposed seven factors of lending relationship quality namely, trust, communication quality of relationship, amount of information sharing, long-term relationship orientation, satisfaction with the relationship, closeness and commitment as the independent variables to the dependent variables which consist of lending relationship quality and how it relates to satisfaction and retention.

Keywords: Banks, Customer relationship marketing, Lending relationship quality Index, SME

Banks’ Lending Relationship Quality Index (LRQI) for the Small and Medium-Sized Enterprises: A Review

1. Introduction

A competitive environment is one of the antecedents of relationship marketing (Sheth and Parvatiyar, 1995). As such, relationship marketing tends to be more focused on establishing, keeping customers and enhancing the relationship with them (Storbacka, Standvik and Gronroos, 1994). Developing a strong customer relationship has been considered as an avenue for gaining competitive advantage (Reichheld, 1993) as the intangible aspects of a relationship are not duplicable by the competitors (Athanasopoulou, 2008). However, companies are striving to increase their market share. These challenges would require marketers’ continuous effort to retain their satisfied customers and to seek new customers.

2. Lending Relationship Quality Index

The study of relationship marketing has attracted growing attention since 1990 as marketing approaches have inclined toward relational exchange approaches from discreet transaction approaches. Relationship quality is an extended issue of relationship marketing (Alwie and Bojei, 2010). Though relationship quality originates from service quality paradigm, the concept of relationship quality has been understood as the quality of relationship (Lehtinen and Jarvelin, 1995). The concept of lending relationship and relationship lending have been interchangeably used in the lending relationship pieces of literature. It is a lending practice that involves the granting of credit if close ties exist between firms and banks (Stein, Memmel and Schmieder, 2008). Previous studies have emphasized different relationship contextual settings (Holmlund, 2007). Ndubisi and Wah (2004) had examined the relationship between the banks and their customers but not specific to lending relationship between the banks and their specific borrowers’ segment (SME borrowers). Though quantitative credit scoring methods have been introduced, relationship-based marketing paradigm still has theoretical relevance as credit evaluation still involve discreet human interactions and contacts. It will remain an integral part of credit risk management processes (Moller and Wilson, 1995). As lending relationship quality aspects have been side-lined by previous researchers, this study will fill the void by identifying factors that presume to influence lending relationship quality and to develop a new lending relationship quality index uniquely designed to assess lending relationship quality for the SME sectors. The new measuring instrument will be empirically tested for multi-dimensionality, reliability and validity by employing both exploratory and confirmatory factor analysis. The findings from the study will add value to the existing literature on lending relationship by hypothesizing the proposed seven factors of lending relationship quality namely, (1) Trust, (2) Communication Quality of Relationship, (3) Amount of Information Sharing, (4) Long-term Relationship Orientation, (5) Satisfaction With The Relationship, (6) Closeness and (7) Commitment as the Independent Variables to one Dependent Variable which is (1) Lending Relationship Quality index (LRQI) as exhibited by the proposed conceptual frameworks (Figure 1). The study will seek to determine how LRQI will relate to retention and satisfaction.

Figure 1: Proposed conceptual framework

2.1 Trust

Trust has been particularly associated with the development of interest in relationship marketing in general and particularly in the context of B2B markets. Trust and its important contribution to loyalty will leave a major impact on how B2B relationships are developed and managed. Parasuraman et al. (1985) introduced trust as a critical success factor in successful service relationships. They suggest that customers need to feel safe in dealing with suppliers and need to be assured that their interaction is confidential so that they can trust their suppliers. Berry (1995) also suggests that “relationship marketing is built on the foundation of trust”. In addition, trust is an important aspect in the development of quality relationships built through a process of making and keeping promises (Dwyer et al., 1987; Gronroos, 1990). Based on the above discussion, the hypothesis is proposed as follow:

H1: Trust positively influences the quality of the banks’ lending relationship with the SME borrowers.

2.2 Commitment

Customer commitment to the supplier motivates customer loyalty in service industries (Fullerton, 2003). Commitment has been an important dimension of relationship quality (Hennig -Thurau et al. 2002). Commitment is also considered an important ingredient in successful relationships (Morgan and Hunt, 1994). It refers to the motivation to stay with a supplier or suppliers (Moorman et al. 1992). Geysken et al. (1996) also provided empirical evidence that the relationship of customer commitment to future purchase intentions and intention to stay if the relationship exists. Based on the above discussion, the following hypothesis is proposed:

H2: Commitment positively influences the quality of the banks’ lending relationship with the SME borrowers.

2.3 Amount of Information Sharing in Relationship

The amount of information sharing is defined as the extent to which the supplier openly shares information that may be useful to the relationship with the buyer (Cannon and Homburg, 2001). In the context of SME borrower, the definition can be literally “borrowed” as the extent to which the loan processing officers can openly share information that may be meaningful to the relationship with the SME customers. The definition may refer to how long and how frequent the SME customers and loan processing officers enter into contact with each other (Farace et al., 1977). Hence, the following hypothesis is proposed:

H3: The amount of information sharing in the relationship positively influences the quality of the banks’ lending relationship with the SME borrowers.

2.4 Communication Quality of the Relationship

Mohr et al., (1996) identified communication difficulties as a major cause of problem between the parties to the relationship. Communication depends on the information of various types. However, it cannot be construed with the sending or receiving information for that matter. Hence, the proposed hypothesis is as follows:

H4: Communication quality of relationship positively influences the quality of the banks’ lending relationship with the SME borrowers.

2.5 Long-Term Relationship Orientation

Firms can sustain competitive advantage by nurturing long-term relationship (Ganesan, 1994). From exporting perspective definition, Ganesan (1994) argues that long-term relationship is a perception of mutual dependence of outcomes in such a way that mutual relationship outcomes are expected to benefit from the relationship in the long run. Similarly, a relationship orientation may also be applied the other areas of banking such as Investment Banking Boot (2000). Long-term relationship orientation captures exporter’s desire to develop a long-term relationship with the importer, namely, in terms of long-run profitability and maintenance of the relationship, long-term goals and long- run concessions. Hence, the proposed hypothesis is:

H5: Long-term Relationship Orientation positively influences the quality of the bank’s lending relationship with the SME borrowers.

2.6 Satisfaction with the Relationship

Kotler (1994) states “the key to customer retention is customer satisfaction”. There is much theoretical and empirical evidence that shows the linkage between satisfaction and customer retention and customer loyalty. Aaker (1988) states that satisfaction is a key determinant to every level of brand loyalty. Oliver (1993) suggests satisfaction is to be an effective antecedent of brand loyalty. Oliver (1981) proposes three dimensions of satisfaction; cognitive, affective and conative, that culminate in action loyalty or repeat usage. In consumer marketing, there is consistent evidence that satisfaction contributes to repurchase intentions, behavioral intentions, customer retention and customer loyalty (Anderson and Sullivan, 1993). Based on the above discussion, the following hypothesis is postulated.

H6: Satisfaction with the relationship positively influences the quality of the bank’s lending relationship with the SME borrowers.

2.7 Closeness

Closeness is a frequently used dimension for an understanding of B2B relationship (Neilson, 1998; Auh, 2005). However, there have been few studies that have examined closeness as a predictor in a high-quality relationship in the customer markets. Guenzi and Pelloni, (2004) contended that closeness can affect the overall customer satisfaction, behavior loyalty (usage frequency), personal loyalty toward the service employee and loyalty intention. However, this factor is relevant for this study and the proposed hypothesis is:

H7: Closeness positively influences the quality of the banks’ lending relationship with the SME borrowers.

2.8 Satisfaction and Retention

A confirmation/disconfirmation theory (Oliver, 1981) explains that satisfaction is achieved when expectations are fulfilled (confirmed). A negative disconfirmation of e expectations will result in dissatisfaction and that positive disconfirmation of expectation will result in enhanced satisfaction. This theory is in line with (Jarvline and Lehtinen, 1996) who argue that RQ refers to a customer’s perception of how well the whole relationship fulfills the e expectations, predictions, goals, and desires the customer has concerning the whole relationship. Hence, it is hypothesized that:

H8: Lending relationship quality positively impacts SME borrowers’ satisfaction.
H9: Lending relationship quality positively impacts SME borrowers’ retention.

3. Methodology and Discussions

The aim of this research was to develop a new lending relationship quality index (LRQ Index) by employing both qualitative and quantitative methods. It has become a dynamic measuring instrument which would be used to assess the quality of a relationship between the banks and their SME borrowers in the context of lending relationship.

3.1 Target Population, Sample Respondents and Sample Size

The five SME Zones of a Premier Bank that are strategically located in Kuching (two ones and one zone each in other towns such as Sibu, Bintulu and Miri were selected for the pilot test from which the sample respondents were generated. The Premier Bank has forty (40) SME Zones throughout Malaysia. A pilot sample size of one hundred (100) were drawn from all the five SME Zones in Sarawak who were invited to participate in the face-to-face interview. A pilot sample size of 100 was deemed sufficient which was within the guideline. Roscoe (1975) proposes based on rule of thumb, a sample size larger than thirty (30) and less than five hundred (500) are appropriate for most research (Sekaran, 2010, pp 296). During the structured one to one interviews, the pilot sample respondents were asked to describe various aspects related to the relationship. The banking industry provided an appropriate setting for service quality model as well as relationship quality (Lassar, Manolis and Winsor, 2000). Customer satisfaction was known to be a vital element of successful operations for banking services (Reichheld and Sasser, 1990).

3.2 Sampling Frame, Sampling Design and Questionnaire Design

The collaboration from all the five SME Zones to provide an up-to-date list of their 20 top SME business borrowers comprising sole-proprietorships, partnerships and private limited companies was proposed. These borrowers were segmented in accordance with BNM definition of SME. The up-to-date list was required in order to minimize the “coverage error”. If the discrepancy between the target population and sampling frame become apparent, the error could be dealt with by either redefining the target population in terms of the sampling frame, screening the respondents or adjusting the collected data by a weighting scheme to counterbalance the coverage error. A Convenient Sampling was selected and care was taken to randomize the data collection. Data was collected using the ‘personal-contact’ approach. The contact persons (SME Managers) were approached to whom the survey procedures have been explained in detail. The final questionnaires together with a cover letter were delivered personally or mailed to the ‘contact persons’ who have distributed it to their customers. The cover letter will ensure the respondent’s strict confidentiality and emphasize the independent nature of the research.

The literature review together with a series of in-depth interviews have become the foundation for capturing the relevant items that were presented in the draft questionnaires. The items were presented randomly as statements on the questionnaires, with the same rating scale used throughout. The items were measured on a five-point Likert-type scale that varies from 1=strongly disagree to 5=strongly agree. The main scale addressing individual items, the sample respondents were required to provide an overall rating on three of the dimensions namely, quality of lending relationship, satisfaction and retention. Utilizing open-ended questions was suggested to allow the respondents the opportunity to express their personal views and opinions on how any aspect of their relational experience with the banks have affected them and how could it be further improved. It was proposed that the draft questionnaires were administered for pilot testing with approximately one hundred samples of SME borrowers drawn from all SME Zones in Sarawak. The findings from the pilot test were empirically tested for reliability to ensure consistency and stability of the questionnaire instrument. Additionally, it has been suggested that validity check has also be carried out to confirm that the instrument the concept of study. Finally, the revised instrument was further subjected to fine-tuned processes based on the constructive feedback from at least five (5) carefully selected experts (policymakers, academics and practitioners) before it was administered on a full-scale survey.

3.3 Factor Analysis

Exploratory Factor Analysis (EFA) was used to identify the dimensional structure of factors contributing to lending relationship quality in the SME business borrowers’ segment by employing exploratory and confirmatory to assess the dimensionality of the lending relationship quality index. One critical assumption underlying the appropriateness of factor analysis was to ensure that the data matrix has sufficient correlations to justify its applications. Factor analysis has involved three critical steps as follows:- (i) The first step has involved the visual examination of the correlations to identify those data matrix that was statistically significant. A data matrix that indicates the correlation of above 0.3 or p < 0.01 has been considered substantial for factor analysis, (ii) The second step has involved the assessment of the overall significance of correlation matrix by using Bartlett test of sphericity. This test has provided the statistical probability that the correlation matrix has significant correlations among at least some of the variables. The desired correlation must be at p < 0.01. This was to assess whether the data were suitable for factor analysis and (iii) The final step of the factor analysis has involved the measuring of sampling adequacy by using Kaiser-Meyer-Olkin (KMO) technique to quantify the degree of intercorrelations among the variables which could be identified by an appropriate index (Kaiser, 1970) ; (0.9 = marvelous); (0.80 = meritorious); (0.70 = middling) ; 0.6 = mediocre); (0.50 = miserable); and (< 0.50 = unacceptable). Exploratory factor analysis was a useful preliminary technique for developing the survey instrument (questionnaire) but a subsequent confirmatory factor analysis was necessary to refine the resulting instrument for unidimensionality. Unidimensionality refers to the existence of a single construct underlying a set of measures, and it has been computed by means of structural equation modeling within LISREL framework. Exploratory factor Analysis will involve two major steps as follows:- (i) All the proposed items of the questionnaire have been subjected to factor analysis by employing the maximum likelihood procedure that was followed by a Varimax rotation. This was done to determine which variables were included in the factor loadings. A variable which indicates factor loading greater than 0.5 (Hair et al., 1995) was included. Factors whose eigenvalues of greater than 1.0 were retained in the factor loading (ii) The next step was to assess the communality of each variable in order to decide which item loadings were worth considering in explaining the factors. The variable’s communality, which represents the amount of variance accounted for by the factor solution for each variable were assessed to ensure an acceptable level of explanations. If the communalities in the variables were below 0.50, they were considered too low for having sufficient explanation (Hair et al., 1995).

3.4 Confirmatory Factor Analysis (Cfa)

The Goodness-of-fit (GFI) was generally considered as the most reliable test of absolute fit in most circumstances. A GFI and Adjusted GFI indices of between 0 and 1 and value of greater than 0.90 were considered an acceptable fit. These indices have indicated evidence of unidimensionality for the scale. Once unidimensionality of the instrument was established, its statistical reliability was assessed before it was subjected to any further validation analysis. The reliability measurement indicated the stability and consistency with which the instrument measured the concept.

In this study, two internal consistency estimate of reliability namely coefficient alpha called Cronbach’s alpha and split-half coefficient expressed as Spearman-Brown corrected correlation were computed for the seven factors of lending relationship quality. An alpha value of 0.70 and above has been considered to be the criterion for demonstrating internal consistency of the survey instruments (Nunnally, 1978). If all the values are able to meet the desired prerequisite of 0.70 and above, then it indicated that all the factors were considered consistent internally and have satisfactory reliability values in their original form.

3.5 Convergent and Discriminant Validity Test

These have involved assessing the validity of the constructs if a set of measures correctly represents the concept of study. The questionnaire was appropriately designed through a comprehensive review of the relevant literature as well as subject to rigorous fine-tuned based on the suggestions from the experts in the field. This was done to ensure that both the face and content validity of the measuring instruments were able to measure what was supposed to measure. Convergent validity refers to the degree to which the different approaches to construct measurement are similar to (converges on) other approaches that it theoretically should be similar. When there is a high correlation between a measure and other measures that are believed to measure the same construct, convergent evidence for validity is obtained. The correlation among the seven factors of lending relationship quality was computed to assess for their convergent validity. If the correlation coefficient has indicated values between 0.70 and 0.80, it indicated a moderate positive relationship among the seven factors of lending relationship quality. Thus, there was evidence of convergent validity. The problem of multi-collinearity will not become a major issue if the correlation value is lower than 0.8 (Kline, 1998).On the other hand, discriminant validity will be determined by verifying whether the dimensions/constructs are differentiating factors or form the same factor. The instrument will be tested for discriminant validity using a Chi-square difference test. A Chi-square difference test will be used to test the scale for discriminant validity. In this study, all the discriminant validity tests on all the seven factors of lending relationship quality will be performed and the test must show that they are statistically significant at the p=0.01 level, thus indicating that the factors are distinct variables and, discriminate from each other. Additionally, criterion-related validity will be established by correlating the factors scores with other constructs. In this study, criterion-related validity is established by correlating the factor scores with lending relationship quality construct.

3.6 Multiple Regression Analysis

Finally, multiple regression was used to determine the overall influence of the key factors on lending relationship quality. The regression model would consider the lending relationship quality level as dependent variable and the lending relationship quality scores for the individual factors as the independent variables. A multiple regression analysis was subsequently conducted to evaluate how well the seven factors can predict the quality of the lending relationship between the banks and their SME borrowers. The linear combination of the seven factors was correlated with lending relationship quality as dependent variable to determine the coefficient of determination (r²). The coefficient of determination was useful because it could provide the proportion of variance (fluctuation) of one variable that was predictable from the other variable. Regression analysis was also applicable to assess the impact of lending relationship quality on customer satisfaction and retention. The regression analysis was carried out to show whether lending relationship quality has a significant impact on satisfaction as well as retention. In addition, regression analysis was used to assess whether the hypotheses could be supported or not.

4. Conclusion and Recommendations

The lending relationship quality conceptual frameworks (Figure 1) presented in this study was the first attempt to bring relationship quality into account in lending perspectives and to describe and clarify the concept of lending relationship quality. It also broadened the traditional relationship quality view into the areas which have not been explored (Lending relationship quality). The review of previous literature on the lending relationship has shown researchers’ interest in other relationship contextual settings which were not specific to lending relationship quality between the banks and their specific borrowers’ segment (SME borrowers). Though banks have embarked on quantitative credit scoring, it is contended that relationship-based marketing paradigm will continue to have theoretical relevance since credit evaluation would still involve discreet human interactions and contacts that will remain an integral part of credit management processes. The concept of lending relationship quality in this paper may directly affect seven bonding variables namely, t rust, commitment, amount of information sharing, the communication quality of the relationship, long-term relationship quality, satisfaction with the relationship and closeness. These bonding variables are to be hypothesized in order to develop a new lending relationship quality index to assess the quality of lending relationship between the banks and their SME borrowers. The new measuring instrument will be further tested on how it can relate to satisfaction and retention.

The results from this study are crucial because the previous study on RQ produced scale might not be totally adequate to assess the RQ in bank-SME borrowers perspective, thus paving way for other researchers to perform further investigation to improve RQ scale in the banking industry. Through the findings of this study, the Bank’s management will be able to identify critical dimensions of LRQ in order to improve the bank’s RQ performance and subsequently create competitive advantage. It is expected to provide guidance to the Branch Manager, SME Manager and Relationship Officers of the banks on how to manage customer relationship in a more objective and satisfied manner and hence, to enhance SME borrowers’ retention. Consequently, the findings from this study will contribute further to the fast growing literature on Relationship Quality (RQ) by advancing a new measuring instrument of lending relationship quality which is specially designed for SME banking outfits in Malaysia.


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