Further Probing Satisfaction in Banking

7/29/2019 Further Probing Satisfaction in Banking

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Further probing of higher order insatisfaction construct

The case of banking institutions in Malaysia

Ding Hooi TingSchool of Business and Economics, Monash University Malaysia,

Selangor, Malaysia

Abstract

Purpose This paper aims to bring a new insight by examining the satisfaction model in a morecomplex manner to capture the variations of the satisfaction construct better.

Design/methodology/approach The paper presents a subsequent expansion from a previousresearch. The methodology used is similar, as the researcher believes that it is the best way to measure

and to capture the curvilinear relationship of the variables under study. Regression of a higher formhas been discussed and established and three variables were tested, i.e. word-of-mouth referrals(dependent variable), satisfaction (independent variable), and ownership (moderating variable). Inorder to test for the moderating effect, the hierarchical moderated regression analysis has beenemployed.

Findings This study contributes to the body of knowledge in two ways. First, a literature reviewand exploratory study suggest that marketers should consider a higher-order model in the models ofsatisfaction. Second, further considerations should be made to determine the curvature of therelationship where the researcher suggested that there might be a U-shaped relationship betweensatisfaction perception and word-of-mouth referrals when there is a change in ownership.

Research limitations/implications Customer satisfaction should be seen as a non-linearconstruct. In fact, in most industries there are tendencies to build marketing strategies around theircore services. However, this research suggests that customers in Malaysia view beyond satisfaction in

choosing their banks. Malaysian bank customers prefer patronizing banks from the same ethnic groupas theirs, where banks owned by the same ethnic group as the customers are able to moderate thesatisfaction level.

Originality/value The paper shows and suggests how satisfaction construct should be measuredin a non-linear form with interaction in a different cultural context as in the banking sector inMalaysia.

Keywords Customer satisfaction, Banking, Malaysia

Paper type Research paper

IntroductionThere have been extensive studies in the West to test the satisfaction construct andhow it affects word-of-mouth referrals. New models have been developed and tested inorder to gain better insights into the customer satisfaction construct. However, thereare few studies conducted in Asian countries, especially Malaysia on the satisfactionmodel. Most of the models developed consider the use of a linear model to test thesatisfaction construct. A recent development in the satisfaction literature suggests thatthe satisfaction construct should be in a non-linear form (Anderson and Sullivan, 1993;Basadur and Head, 2001; Oliva et al., 1992; Taylor, 1997). The purpose of this paper isto assess this argument in a different cultural context as in the banking sector inMalaysia.

The current issue and full text archive of this journal is available at

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IJBM24,2

98

International Journal of Bank

Marketing

Vol. 24 No. 2, 2006

pp. 98-111

q Emerald Group Publishing Limited

0265-2323

DOI 10.1108/02652320610649914
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The objective of this study is to have a better grasp of the relationship patternbetween the word-of-mouth referrals and satisfaction with ownership as the moderatingvariable as opposed to the widely used linear model. The researcher will further probeinto the higher order and the curvature of the relationship. Hence, the first objective of

this study is to further probe the curvature of the higher order model[1] of therelationship under study. The second objective is to test the simple slope and the natureof the relationship under study where ownership by certain ethnic groups will be used asthe moderator between satisfaction and word-of-mouth referrals.

Literature reviewWord-of-mouth marketing tends to work very slowly and it is limited geographicallybut it is a very effective method of marketing. The value of word-of-mouth marketingis immense because of its impartiality and credibility from the customers point of view(File et al., 1992). Word-of-mouth referrals are important in determining the success of abank and are the cheapest method for a bank to market itself. It needs no additionalcosts for advertising in local newspapers or in any media.

In many situations, customers seek the opinions of others before selecting a servicefirm. When customers depend on someone else for information (other customersexperiences) as opposed to the companys advertisements, the beliefs they hold aboutwhat the product will do (expectations) may be important in forming satisfaction (Goodeet al., 1996). Customers referrals act as a better guide compared to advertisements sincethe screening process has taken place in the recommenders mind. In the study by Tanand Chua (1986) in Singapore, they found that friends, neighbors and family membershave great influence on prospective customers when it comes to making decisions as towhich financial institution to patronize. These findings are consistent with the Easternculture that puts emphasis on social and family ties (Haron et al., 1994).

Many marketing researches on service quality and customer satisfaction found thatthey have a unique and strong relationship (Cronin and Taylor, 1992; Zeithaml et al.,

1993) whereas Boulding et al. (1993) and Zeithaml et al. (1996) did not differentiatebetween service quality and customer satisfaction, but treated them as the same entity.Satisfaction is the outcome of ones experiences and the ability of the supplier to

meet the norms and expectations (Dwyer et al., 1987; Fornell, 1992; Oliva et al., 1992).The studies done by Fornell (1992) and Cronin and Taylor (1992) show that satisfiedcustomers would have effect on subsequent behavior after purchase. In other words,satisfaction would lead to positive word-of-mouth referrals and vice versa.

Bank ownershipIn Malaysia, there are three major types of bank ownership owned by the three majorethnic groups, that is the Malays, Chinese and Indians. The government has tried tointegrate the multiracial and ethnic groups in Malaysia into one identity through

various means and approaches ever since her independence in 1957.The study carried out by Edris (1997) on the quality that is regarded as importantfor business customers and the determinants on bank selection among the Kuwaitisfound that local ownership is one of the determinants for bank selection; whereas astudy by Athanassopoulos (1997) showed that there is no global difference between theprivate and the government-owned banks; this has been further confirmed byKristensen et al. (2001). These researchers researched on customer satisfaction andloyalty in retailing, to investigate possible effects of ownership and type in Danishretailing. They found out that there are differences in image between privately-owned

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stores and stores owned by a co-operative where privately-owned stores lead to highercustomer loyalty and customer compared to stores owned by a co-operative.

While a study carried out by Martnez-Tur et al. (2001) shows that as the number ofdistinct services an organization offers (structural complexity) increase, public

organizations are less able to maintain customer satisfaction than privateorganizations. In other words, ownership appeared to have impact on therelationship between service structural complexity and customer satisfaction.

From the reviews above, it is hypothesized that ownership would be able tomoderated the relationship between satisfaction and word-of-mouth referrals.

Curvilinear and higher orderAccording to Kano et al. (1984) and Taylor (1997), there are many literatures thatsuggest that evaluation of satisfaction should involve a curvilinear and higher orderform. However Taylor and Baker (1994) included the interaction effect as well. This hasbeen confirmed by Conklin et al. (2004), Danaher (1997), Oliva et al. (1992) and Ting(2004) who stated that the satisfaction model should not be in a linear form.

Customer satisfaction has also been seen as a non-linear model leading tosubsequent behaviors (Anderson and Sullivan, 1993; Coyne, 1989; Oliva et al., 1992;Rust et al., 1994, 1995, 1996). In other words, the relationship between satisfaction andits outcome should also be non-linear. However, Jaccard et al. (1990) showed that therelationship between the two different variables should be represented by a cubicfunction (X3). According to Aiken and West (1991), failure to express the function in acurvilinear form and interaction effect will lead to an error in the interpretation whichmay sometimes be very serious.

While in a study by White and Yu (2005), it was found that there is no curvilineareffect between the emotions and behavioral intention scales (positive word of mouth,complaining behavior, switching behavior and willingness to pay). According toBusacca and Padula (2005), failure to account properly for the non-linear and

asymmetric relationship between attribute performance and overall satisfaction wouldlead to incorrect prioritization of resource allocation to enhance customer satisfaction.The above reviews denote some arguments to the literature on the curvilinear

nature of satisfaction construct. As there has been support from previous research plusthe dynamism of customer behavior, it is therefore hypothesized that there exists acurvilinear nature for the satisfaction construct.

MethodologyThe sample for this study was gathered via a snowballing method where the initialsamples chosen were randomly selected. The snowballing method was adapted asthere was no ready-made frame that could capture the entire population. Respondentsare between 21 and 60 years of age because this category had the most working in the

age group. A total of 2,100 questionnaires were distributed and 51 percent of thequestionnaires were returned.Questionnaires used in this study focus on the word-of-mouth referrals, satisfaction

of bank customers and bank ownership of the same ethnic group as the customers.The following method will be used to test the relationship between word-of-mouth

referrals and satisfaction with the ownership as the moderator. There are four itemsused for the word-of-mouth referrals: possibility of telling positive aspects of a bankto acquaintances; possibility of referring a bank to acquaintances who asked about it;possibility of telling acquaintances about a bank in general; and possibility of

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describing in detail about a bank to acquaintances using a Likert scale of 1 to 7where 1 refers to very unlikely and 7 refers to very likely. As for satisfaction,only one item was used according to Cronin and Taylor (1992) The item used wasMy feelings towards XYZs services can best be described as . . . in a seven-point

Likert scale ranging from 1 (very unsatisfied) to 7 (very satisfied). As forownership, one item was used, this is Ownership of banks by Malays. Both thesatisfaction and bank ownership questions used a 1 to 7 scale where 1 isstrongly disagree and 7 is strongly agree. Equation (1) is the basic equationused to study the relationship between two independent variables and a dependentvariable (Aiken and West, 1991):

Y a1 a2X a3Z e 1

Y a1 a2X a3Z a4XZ e 2

Y a1 a2X a3X2 e 3

Y a1 a2X a3X2 a4Z e 4

Y a1 a2X a3X2 a4Z a5Z Z e 5

Y a1 a2X a3X2 a4Z a5XZ a6X

2Z e 6

Y a1 a2X a3X2 a4Z a5Z

2 a6XZ a7X2Z a8XZ

2 a9X2Z

2 e: 7

The equations above are similar to those used by Ting (2004) because the researcher

thinks that it is the best approach to measure the interaction and curvilinear effect(Aiken and West, 1991). Equation (1) suggests that the subsequent behavior after apurchase, i.e. word-of-mouth referrals (Y) is a function of a constant (a1), plus theregression coefficient for satisfaction (X) with the moderating effect, ownership (Z)and the error term (e). Equation (1) is the most basic model. The coefficient X showsthe slope of the regression line that can best predict the independent variable (Taylor,1997) whereas equation (2) is an extension of equation (1) that includes the interactionterm. Aiken and West (1991) have found a few models that have the potential tocapture a more complex relationship using a higher order form which has proved tobe more consistent. The change in the regression form to a higher-order form istermed as curvilinear model. The most basic curvilinear model is shown in equation(3). Here, the predictor Xhas a curvilinear relationship with Y i.e. Xand X2 represent

the linear and quadratic components of the total effect. Equation (4) suggests that theregression Y on X is curvilinear whereas the regression Y on Z is linear. Equation (5)shows a model that has a linear interacting effect on top of the curvilinearrelationship of X and Z. The difference between equations (4) and (5) is that therelationship between Y on X and Y on Z is no longer parallel. Equation (6) isexpanded to show the curvilinear and interaction effects for X and Z whereasequation (7) shows the example of a higher-order model or an interaction effect thathas a curvilinear effect. In order to show the two-way interaction, four additionalcomponents have been added into the equation. They are XZ, X2Z, XZ2 and X2Z2.


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Here, they show the curvilinear relationship ofX, curvilinear relationship ofZ, and allpossible interactions. This model suggests that the curvilinear relationship exists inboth the independent variables and its interaction.

In order to test the hypotheses that a curvilinear satisfaction model explains more

variations than the linear model, hierarchical moderator regression will be utilized.Here the moderating effect is also included.

Identifying the curvilinear nature of independent variableIn order to identify the curvilinear nature of the independent variable, the followingequation will be employed:

Y a1 a2X a3X2 a4X

3: 3a

To determine the existence of interaction and quadratic effects in the models tested,Table I will be used. In each model, there will be two similar dependent variables butthe independent variable will be different. This is to test whether any interaction andquadratic effects exist between the two different variables. For the second level, if Fchanges, then the test is significant. It means that there are quadratic effects and thetest on quadratic effects on the interaction effects is carried out using the equations (7),(2) and (1) as suggested by Taylor (1997). If only one equation has a quadratic effect,models 6, 5 and 1 will be used (Taylor, 1997). If both equations are not significant, thenthere are no quadratic effects and the model is linear.

The findings from Table I show that there exist quadratic effects (that is X2) andinteraction effects on the dependent variable, that is satisfaction. The term, X3 isinsignificant statistically, and does not add to the prediction ability as seen by thechange in R2. According to Aiken and West (1991), the relationship between theindependent and the dependent variables with cubic forms is very rare. The findingssupport the fact that there might exist a non-linear form for satisfaction. Equation (6)

represents the step-down procedures since it includes the quadratic function (X2) andthe linear function (XZ) as well as the linear-quadratic effect (X2Z).

While the step-down procedures in the hierarchical moderated regression as inequations (5) and (6) may show the potential existence of multicollinearity, the removalof the scale-dependent[2] term demonstrates that issues related to multicollinearity tothe final results are no longer present (Taylor, 1997). Furthermore, multicollinearity isan issue for linearly dependent models.

Model R2 DF

Y 3:246** 0:344X1 2 0:0509X1 0:006485X31 0.103 0.646

Y 3:787** 2 0:05467X1 0:0398*X21 0.103 0.046

*

Y 2:984** 0:317**X1 0.099 0.000 * *

Y 3:454ast; ast; 0:503Z2 0:105Z2 2 0:00896Z3 0.043 0.251Y 3:924** 0:0677Z 0:009624Z2 0.042 0.487Y 3:761ast; * 0:153**Z 0.041 0.000 * *

Notes: * Significant at 0.05 level; * * Significant at 0.01 level; Y refers to word-of-mouth referrals;X1 refers to satisfaction; Z refers to ownership

Table I.Examining thecurvilinear nature ofmodel

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Post hoc probing of a more complex regression equationIn order to assess further the relationship of the underlying variables, the procedure ofprobing using a simple curvilinear equation (second order) involving only Xand X2 asin equation 3 were carried out:

Y a1 a2X a3X2 e: 3

This equation can be re-written to show the regression of Y on X:

Y a2 a3X X a1 e: 8

From equation (8), the regression ofYon Xdepends on the specific value ofX; that is atany particular value of X, the value of Y might be decreasing, not changing at all orincreasing. The regression slope of Yon X as in equation (3) is no longer a2 a3Xbut a2 2a3. The approach of re-arranging the regression equation to identifysimple slopes does not generalize to equations containing curvilinear components.

Simple slope derivation from the regression equationThe mathematical operation involving derivations (in order to obtain the tangent slopeof a curve on a particular point) will give the regression measurement of Yon X at aparticular value of X along the curve. The slope for regression of Y on X is the firstderivative of the regression equation of Y on X on at least one variable or othervariables such as Z, the variable X itself or the combination of variables. Hence:

DY=DX a2 2a3X: 9

When a particular value ofXi is substituted into equation (9), then the value obtained isthe simple slope of Y on X at that particular value of Xi.

From Table II we can see that satisfaction and ownership explain a significantamount of relationship in word-of-mouth referrals (R2 0:103, r, 0:01) whereas inthe partial quadratic interaction effect at level three, the ownership variable explains asignificant amount of effect in word-of-mouth referrals (DR2 0:007, r, 0:05).

Simple slope and the nature of the curveSince it is difficult to interpret the relationship ofYon Xas in equation (6) above, theequation is rewritten as follows:

Y a2 a5Z X a3 a6Z X2 a4Z a1 : 6a

As in equation (6), the coefficient of a2 a5Z provides the same information as thecoefficient a2 in the overall equation. On the other hand, the coefficient a3 a6Zrepresents the linear term of Xon Yon the value of Z that is equal to a3. It represents

the curvilinear nature of a simple regression line. If the value ofa2 a5Z is positive,then the curve will slope upwards and if it is negative, then it will slope downwards.By re-writing equation (6) in full, the following will be obtained:

Y 5:7152 0:939X2 0:533X2 0:135Z 0:229XZ2 0:034X2Z e:

By using the parameter values in equation (6a), the equation below is written:

Y 20:939 0:229ZX 20:533 0:034ZX2 0:135Z 5:715:


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In order to obtain the slope of Equation 6a, substitute the values of22.200, 0 and 2.200withZL (Zbelow),ZM(Zmean) andZH(Zabove)[3]. The values of Z will then be substituted intoequation (6a). The value ofa2 a5Z is negative but the negativity becomes lesser asZincreases;Z:21.4428 forZL,20.939 forZMand20.4352 forZL. Hence, equation (6) has anegative slope. However, the values for a3 a6Z are as follows: 20.6078 for ZL,20.533 for ZM and 20.4582. The negativity reduces as the values ofZincrease.

To test the coefficient significance of a2 a5Z and a3 a6Z, the standard

deviation will be calculated (Tables III-IX). The standard regression for computation

Dependentvariable Equation Parameter b Std error R2 DR2 DF D sig. F

Y 1 Constant 2.992 * * 0.146 0.100 0.100 56.438 0.000 * *

X1 0.331 * * 0.040Z 20.0155 * * 0.030

5 Constant 3.817 * * 0.434 0.103 0.003 2.068 0.127X1 0.0026 0.209Z 20.0724 0.115X1 *Z 0.0278 0.028

X12 0.0139 0.024

6 Constant 5.715 * * 1.007 0.107 0.004 4.357 0.037 *

X1 20.939 * 0.497Z 20.533 * 0.249X1 *Z 0.135 * 0.059

X12 0.229 * 0.106

X12 *Z 20.034 * 0.011

Notes: * Significant at 0.05 level; * * Significant at 0.01 level; Model number refers to the equationfrom the manuscript that is empirically accessed in the analysis

Table II.

Partial quadratic for thedependent, independentand moderator

Mean Std deviation

Satisfaction 0 1.2701Ownership 0 1.6924

Table III.Mean and standarddeviation (for centereddata)

Mean Std deviation

Word-of-mouth referrals 4.465 1.286

Satisfaction 0.033 1.272Satisfaction2 23.648 12.034Ownership 20.033 1.694Satisfaction *Ownership 23.302 12.488Satisfaction2 *Ownership 123.279 90.007

Note: The above is computed for the X2Z interaction in the regression equation Y a1 a2Xa3X

2 a4Z a5XZ a6X

2Z e: overall analysis with centered X and centered Z means andstandard deviation

Table IV.Computation of simpleslope analysis bycomputer

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procedure will be used to test the simple slope (Darlington, 1990). Regression analysiswith Xabove and Zbelow in order to derive the simple slope analysis on XH and ZL(regression of Y on X at one standard deviation above the mean value of X, and onestandard deviation below the mean value of Z). Tables III-IX comprise of differentcomponent output from the analyses. From Tables III-IX, for the value of a3 a6Z,atZL, the tvalue 0:022; at ZM, the tvalue 0:031 whereas at ZH, the tvalue 0:027.This further supports the theory that the curvature of regression Y on Z at ZL has adownward sloping trend as Z increases.

The readers should note that the linear coefficient ofa2 a5Z and the curvilinearcoefficient of a3 a6Z in equation (6a) is not a simple slope. But the coefficient

B Std error

Constant 5.715 * * 1.007

Satisfaction 20.939 * 0.497

Ownership 20.533 * 0.249

Satisfaction *Ownership 0.135 * 0.059

Satisfaction2 0.229 * 0.106

Satisfaction2 *Ownership 20.034 * 0.011

Notes: * Significant at 0.05 level; * * Significant at 0.01 level; Dependent variable: word-of-mouthreferrals; for the X2Z interaction in the regression equation Y a1 a2X a3X

2 a4Z a5XZ

a6X2Z e: overall analysis with centered X and centered Z regression analysis

Table V.Computation of simple

slope analysis bycomputer

Mean Std deviation

Word-of-mouth referrals 4.4714 1.2786Zabove 2.9645 1.6939X2A 13.3102 8.8403Zbelow 1.6924 1.6924XAZB 23.1382 12.5039X2AZB 93.9146 75.6825

Note: The above is computed to derive the simple slope at XH and ZL (regression of Y on I at onestandard deviation above the mean of X and one standard deviation below the mean Z) mean andstandard deviation

Table VI.Regression analysis with

Xabove and Zbelow

B Std error

Constant 5.215 * * 0.701Xabove 20.881 0.469X2A 0.175 * 0.076Zbelow 20.243 * 0.124XAZB 0.229 * 0.106X2ZB 20.023 * 0.011

Notes: * Significant at 0.05 level; * * Significant at 0.01 level; Dependent variable: word-of-mouthreferrals

Table VII.

Regression analysis withXabove andZbelow to derive

the simple slope at XHandZL (regression ofYon

X at one standarddeviation above the mean

of X and one standarddeviation below the meanZ) regression analysis


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shows the overall relationship ofYon Xat a particular value ofZ. Hence, in getting the

simple slope of Y on X for equation (6), the first derivation should be done on X:DY=DX a2 2a3X a5Z 2a6XZ: 6b

The simple slope of Yon X depends on the values of both Xand Y. The simple sloperelates to both the possible combinations for XL, XM and XH as well as ZL, ZM and ZHcalculated by substituting the values of X and Z in equation (6b). An example of thecalculation is as follows.For the simple slope ofZH 1:6924 and XL 21:2701, substitute back into equation(6b), thus the simple slope is 20:9392 2 (20.533) 21:2701 0:229 1:6924 2(20.034) (21.2701) 1:6924 21:6407. However, to obtain the standard error, it canbe calculated using the variance of the simple slope that is:

s11 4X

2

s22 Z

2

s44 4X

2

Z

2

s55 4Xs12 2Zs14 4XZs24 4XZs15 8X

2

Zs25

4XZ2s45:

To obtain the standard error, it is the square root of variance.The matrix that includes the nine simple slopes and standard error is as shown inTables X and XI.

Based on the above readings, for example, for combinations ofXL and ZM (Table X,row 1, column 2), the reading for the simple slope is 22.2929. On the other hand, for

Mean Std deviation

Word-of-mouth referrals 4.4714 1.2786Satisfaction 4.6901 1.2709

Satisfaction2 23.6109 12.0132Zabove 21.6924 1.6924XZA 15.3273 10.6361X2ZA 83.0144 71.1914

Note: The above is computed to derive the simple slope at Xmean and ZH (regression ofYon Xat onestandard deviation above the mean of X and one standard deviation below the mean Z) mean andstandard error descriptive statistics

Table VIII.Regression analysis withX and Zabove

B Std error

Constant 4.813 * * 0.700

Satisfaction 20.552 0.358Satisfaction

20.0959 * 0.043

Zabove 20.533 * 0.249XZA 0.229 * 0.106X2ZA 20.023 * 0.011

Notes: * Significant at 0.05 level; * * Significant at 0.01 level; Dependent variable: word-of-mouthreferrals; the above is computed to derive the simple slope at Xmean and ZH (regression ofYon Xatone standard deviation above the mean of X and one standard deviation below the mean Z) regression analysis

Table IX.Regression analysis withX and Zabove

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combinations ofXM and ZM at the mean values of both Xand Z(row 2, column 2), thesimple slope is equivalent to20.939 (the value is the same for the coefficient value ofa2on X in the overall equation). The standard error obtained and the

t-test for all the nine

combinations ofXandZwill be used to determine the slope of the curve. ForXL,itcanbeseen that the simple slope for the regression curve becomes flatter as ZL increases. Thesame applies to XM. As for XH, the slope becomes even flatter as Zincreases.

GraphTo portray the interactions between the moderating variable and the ownership moreclearly, a graph is drawn. To draw the graph, the bases of satisfaction and moderatorvariables are initially re-coded into three categories namely low, moderate and highby dividing the respondents into three approximately equal groups using thefollowing percentile (0 2 33 percent Low, 33.1 66 percent Medium and 66.1percent High).

As can be observed from Figure 1, for low ownership level, as the level ofsatisfaction moves from low to high, the level of influence of word-of-mouth referralswill increase. Nevertheless, the reading remains the same as the level of satisfactionmoves from moderate to high. When the level of ownership is high, as the level ofsatisfaction increases from low to moderate, the level of influence in the word-of-mouthreferrals will decline. However, as the ownership level increases from moderate to high,the level of influence of word-of-mouth referrals begins to increase too. For moderateownership level, the level of satisfaction does not have much impact on the level ofinfluence of word-of-mouth referrals. The findings suggest that when the ownership

a1 a2 a3 a4 a5

a1 0.247 20.02859 0.08968 20.04455 0.005050a2 20.02859 0.003465 20.009079 0.004815 20.0005774a3 0.08968 20.009079 0.06196 20.02541 0.00247a4 20.04455 0.004815 20.02541 0.01118 20.001152a5 0.005050 20.0005774 0.002470 20.001152 0.0001253

Notes: t-test is based on n2 k2 1 df where k 5; * Significant at 0.05 level; * * Significant at 0.01level

Table XI.Sa: covariance matrix for

coefficient a

(1) (2) (3)

ZL 21:6924 ZM 0 ZH 1:6924

(1)

XL 21:2701Simple slope

Std error

t

22.8267

0.8437

2 3.3504 * *

22.2929

0.6422

2 3.5704 * *

21.6407

0.464

2 3.536 * *

(2)

XM 0

Simple slope

Std error

t

21.3265

0.6708

2 1.977 *

20.939

0.5169

2 1.8166 *

20.5514

0.3853

2 1.4311

(3)

XH 1:2701Simple slope

Std error

t

0.1735

0.4671

0.3714

0.4149

0.3491

1.1885

0.6563

0.2478

2.649 * *

Note: A simple slope is obtained by using the equation a2 2a3X a5Z 2a6XZ

Table X.Simple slope4 for

equation Y 5.71520.939X2 0.533X2

0.135Z 0.229XZ20.034X2Z e


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level is high, the satisfaction level will only have impact on the level of influence on theword-of-mouth referrals when it ranges from moderate to high below which thesatisfaction level will not be able to influence the word-of-mouth referrals.

Discussion and managerial implicationsThis study stems from arguments from recent development of the nature of therelationship of satisfaction constructs. Through this study, it has expanded ourknowledge on the nature of the relationship and the curvature of the relationship in thecontext of Malaysian banking institution. The findings from this study may be able to

generalize other settings as Malaysia is moving towards globalization where the inflowand outflow of information is very easy, therefore, the perception of Malaysianstowards the satisfaction construct could be seen as one of universal perception. Butmore researches is required to confirm this.

This study contributes to the body of knowledge in two ways. First, a literaturereview and exploratory study suggest that marketers should consider a higher-ordermodel in the models of satisfaction. Second, further considerations should be made todetermine the curvature of the relationship where the researcher suggested that theremight be a U-shaped relationship between satisfaction perception andword-of-mouth referrals when there is a change in ownership.

The downward sloping curve of word-of-mouth referrals, satisfaction andownership shows that the respondents captured at this initial stage of research

might fall into the second category. This implies that the samples obtained from thisstudy are experiencing bank ownership that they favored. Further research is requiredto further confirm this pattern.

From the study, it is clear that customer satisfaction is essential for the banks toremain competitive in the long run. In fact, in most industries there are tendencies tobuild marketing strategies around their core services. However, this research suggeststhat customers in Malaysia view beyond satisfaction in choosing their banks. Thecustomers not only view satisfaction as important, but they also look at the ownershipof the banks where the ownership of the banks tend to moderate the relationship.

Figure 1.Moderating effect ofownership on therelationship between

satisfaction andword-of-mouth referrals

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Anecdotal evidence as well as that from this research suggests that customers mayremain in a relationship even if they perceive the satisfaction level as less than superiorespecially if they are patronizing a bank owned by the same ethnic group. This isbecause there are three major ethnic groups in Malaysia. They are Malays, Chinese and

Indians. The customers accept the styles and culture of banks from the same ethnicgroups. This leads to customers overlooking minor problems experienced by them.Furthermore, there is a sense of belonging social bonds between the banks owned bythe same ethnic group as the customers and the customers themselves. This furthersuggests that the bonds among customers of the same ethnic group are still strongthough there have been efforts carried out by the government to integrate the threemajor ethnic groups in Malaysia since Malaysia achieved her independence in 1957.

Ownership is found to moderate the relationship between satisfaction andword-of-mouth referrals in a higher order manner. This means that Malaysian bankcustomers prefer patronizing banks from the same ethnic group as theirs where banksowned by the same ethnic group as the customers are able to moderate the satisfactionlevel. In other words, when customers patronize banks owned by their ethnic group,the chances of them remaining with the bank would be higher although their

satisfaction level is not as high. This is because if customers patronize banks owned bythe same ethnic group, they are better able to tolerate the way they are served. Inanother words, these customers more or less understand the employees of the bankwho are usually from the same ethnic group as they are, and who would behave moreor less like themselves. Since their mindset has been pre-adjusted earlier about thebehavior of bankers, hence, the toleration level would be higher. Thus, the tendency toignore minor discomfort they experience while dealing with the bank would be higher.

Ownership of banks by different ethnic groups would also use different designs andcolors, hence, the ambience of banks. The Islamic Bank will go for green while thosebanks owned by the Chinese will use bright or red designs. This is because differentethnic groups fancy different styles and ambience such as the decorations.Furthermore, these two aspects are the first to be noticed by customers when theyenter a bank. As the findings suggested, due to the higher emphasis on ethnic groupownership, banks should be able to provide a more welcoming environment and createsocial ties that are able to bind the customers to the banks.

As this is a normal phenomenon in the Malaysian context (which might be due tocolonialism where the three major ethnic groups were treated differently and alsobecause of their places of residence), it is suggested that banks that intend to branchout should investigate the area where they plan to set up the branch (to determine theethnic groups residing in that area) in order to attract more customers. If a bank isowned by an ethnic group which is different from the ethnic group of the residencewhere a branch is being set up, what can be done is to hire employees from the sameethnic group as the residents in that area in order to be able to fulfill the same ethnicityrequirement and to promote better understanding between bankers and customers.

ConclusionThis paper outlined a newer approach to explore the consequences of the satisfactionconstruct of bank customers. The approach used in this study is more practical interms of customer satisfaction and dynamism compared to the traditional way ofmeasuring satisfaction as it leads to a higher variation explained earlier.

From this study, it is found that there exists a higher order relationship betweensatisfaction and word-of-mouth referrals with interaction effects. The findings provide abetter understanding towards the behavior of customers compared to the linear models.


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It is hoped that the findings from this study can be used as a stepping-stone towards amore vigorous research and study in service quality and customer satisfaction.

Notes

1. Please refer to Ting (2004)

2. See Aiken and West (1991) to learn more about the removal of scale-dependent terms.

3. The values ofZL, ZMand ZHare obtained using the centered data. For further reference, seeAiken and West (1991).

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Further reading

Coyne, K. (1989), Beyond service fads meaningful strategies for the real world, SloanManagement Review, Vol. 30, Summer, pp. 69-76.

Holmlund, M. and Kock, S. (1996), Relationship marketing: the importance ofcustomer-perceived service quality in retail banking, The Service Industries Journal,Vol. 16 No. 3, pp. 287-304.

Parasuraman, A., Zeithaml, V.A. and Berry, L.L. (1988), SERVQUAL: a multiple-item scale for

measuring consumer perceptions of service quality, Journal of Retailing, Vol. 64 No. 1,pp. 12-40.

Corresponding authorDing Hooi Ting can be contacted at: [email protected]


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