An empirical study on measuring operating efficiency and profitability of bank branches 10 10160377 2217(90)90002 s

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282 European Journal of Operational Research 46 (1990) 282-294

North-Holland

Case Study

An empirical study on measuring operating

efficiency and profitability of bank branches

Muhittin O R A L a n d Reha Y O L A L A N

Sciences de l'Administration, Universitd Laval, Ste-Foy, QuObec, P.Q G1K 7P4, Canada

Abstract: This paper discusses the methodology of an empirical study that was employed to measure the operating efficiencies of a set of 20 bank branches of a major Turkish Commercial Bank offering relatively homogeneous products in a multi-market business environment The methodology was based on the concepts and principles of Data Envelopment Analysis (DEA) The results of the study have indicated that this kind of approach is not only complementary to traditionally used financial ratios but also a useful bank management tool in reallocating resources between the branches in order to achieve higher efficiencies It has been also observed that the service-efficient bank branches were also the most profitable ones, suggesting the existence of a relationship between service efficiency and profitability

Keywords: Efficiency, productivity, performance evaluation, banking, mathematical programming

1 Introduction

The primary objective of measuring and

evaluating the operating efficiency of bank

branches in a competitive environment is not only

to position the branches with respect to each other

in terms of their efficiencies but also to gain

insight into the nature of operations so that

managerial measures can be taken to improve

their performance More specifically, the method

of performance evaluation needs to be somehow

linked with the decision models in order to be able

to associate the results obtained with the decision

(Oral, 1986) This requires analytical techniques

that provide means of identifying the relative

strenghts and weaknesses of bank branches be-

yond those available from accounting and finan-

cial ratios

Received November 1988; revised May 1989

Banks, especially in industrialized countries, have been in search of new management tools to improve their performance Most frequently, they have tried to achieve this by improving cash management and offering new services that attract additional funds Management of operations has been usually a secondary concern, partly because this is considered, for some reason, to be less critical to profitability The importance of operating efficiency has been recently put into evidence

by a study done at Citicorp According to one of the findings of this study, a 1% decrease in operating expenses would have resulted in more than 2% increase in net income and earnings per share (Sherman and Gold, 1985)

The operating performance of a bank is usually measured using accounting and financial ratios such as return on assets, return on investments, or similar ratios These ratios of course provide a great deal of information about a bank's finav_,:ial performance when compared with prior periods

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M Oral, R Yolalan / Operating efficiency and profitability of bank branches 283

and with other banks' performance There are

however shortcomings of these measures One is

that financial ratios fail to consider the value of

management's actions and investment decisions

that will affect future as opposed to current per-

formance (Sherman and Gold, 1985) In other

words, financial ratios are short term measures

and therefore may not be appropriate to reflect

the real performance of a bank in the long run,

and they may be seriously misleading Another

limitation is that financial ratios aggregate many

aspects of performance such as operations,

marketing, and financing As Sherman and Gold

(1985) stated, a bank may appear to be perfor-

ming well even if it is poorly managed on certain

of these dimensions, as long as it compensates by

performing particularly well on other dimensions

It is necessary for management to identify and

develop means of improving branch performance

For this purpose, other bank management tools

that compensate for the weaknesses in accounting

and financial ratios are needed It seems that Data

Envelopment Analysis (DEA) is such an ap-

proach The experience gained during this em-

pirical study indicates that DEA can be consid-

ered as an alternative bank management tool to

traditional accounting and financial ratios since it

offers means of more comprehensively assessing

the operating efficiency of bank branches

This paper empirically evaluates the use of the

DEA approach as a bank management tool to

improve the productivity of the branches of a

major Turkish Commercial Bank, and consists of

the following sections The next section, Section 2,

briefly describes the principal characteristics of

DEA within the context of the banking sector

Section 3 gives a background of the banking sec-

tor in Turkey in order to put the discussion in

perspective Section 4 describes the procedure used

in applying the DEA method in 20 branches of

the Commercial Bank Section 5 reports the re-

suits of the DEA evaluation of the 20 branches

Finally, Section 6 concludes the paper

2 The DEA approach in summary

organisations where accounting and financial ratios are of little value, multiple outputs are produced with multiple inputs, and the production

or standard i n p u t - o u t p u t relationships are neither known nor easily identified The term 'relative' is rather important here since an organisation identified by the DEA technique as an efficient unit in a given set may become an inefficient one when evaluated in another set of organisations What DEA does in fact is this It compares organisations' observed outputs and inputs, identifies the relatively 'best practice' units to define the 'efficient frontier' and then measures the degree of the inefficiency of the other units relative to the efficient frontier thus defined Different mathematical forms of the DEA model have been suggested

in the literature The formulation that was used in this study is based on the following form:

M a x i m i z e EB = E UrBYrB E ViBX,B

subject to

E l"lrBYrj ViBXij <~ 1

for j = 1, 2 N, UrB, V,B>~e>O Vr, i, where

=

Xij UrB : UiB :

observed quantity of output r produced by bank branch j,

observed quantity of input i used by bank branch j ,

the weight (to be determined) given to output r by the Base Branch B,

the weight (to be determined) given to input

i by the Base Branch B,

a sufficiently small positive number

The linear fractional programming model above can be transformed into an ordinary linear pro-

tV, B, where t -1 =~'.~vmx m Then the equivalent DEA model, the DEA Model A henceforth, can

be stated as follows

DEA is basically a mathematical programming

technique initially developed by Charnes, Cooper,

and Rhodes (1978, 1979, 1981) to evaluate the

relative efficiency of public sector not-for-profit

DEA Model A

R

r = l

(1)

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284 M Oral, R Yolalan / Operating efficiency and profitability of bank branches

subject to

1

E ~iBXiB = 1,

i=1

~ ~rBY~j - ~ ~°~Bx~j ~ 0

r = l i ~ l

~ r B ' ~iB ~ E • 0 Vr, i

(2)

for j = l , 2 N,

(3) (4)

The DEA Model A above has the following

interpretation within the context of commercial

banking There are N bank branches in the ob-

servation set M, each of which producing R dif-

ferent outputs using I different inputs, and we are

interested in determining the relative efficiency E B

of Base Branch B E ~ with respect to all other

branches in the set M The relative efficiency E B

is nothing but the ratio of weighted outputs (also

termed virtual output) of the Base Branch B to its

weighted inputs (also termed virtual input) Such a

definition of efficiency transforms the multidi-

mensional nature of inputs and outputs into a

single scalar ratio of single virtual output to a

single virtual input The objective is to assign the

highest possible value to E B by comparing the

observed outputs and inputs of all bank branches

in the set ~ such that none of the bank branches

has an efficiency index greater than 1 This means

values o f / ~ B ' s and ~0~B's, but consistently due to

the constraints in (3), such that the results favour

the Base Branch B most It is ' m o s t favourable' in

the sense that ~ B ' s and ¢0iB's are optimally de-

termined from the viewpoint of the Base Branch B

and are used to calculate the efficiency of the

other branches in (3) Changing the Base Branch

B of course results in a different set of weights

and efficiency values Although it is favourable to

the bank branch being evaluated, DEA Model A

still provides a means of consistently obtaining the

values of ~rB's and ~0~'s, which may not corre-

spond to the values that a bank manager would

otherwise assign to outputs and inputs Another

point to be made here is that E B ~< 1 since the

efficiency of the Base Branch B is also a member

of the constraint set in (3) In summary, the DEA

Model A provides an ex post evaluation of how

efficient the Base Branch B was with the actual

inputs xi~'s used to produce its actual outputs

y~a's without explicit knowledge of the i n p u t - o u t - put relationships or production function it used

In this context, the data set consists of x~j's and

y r f s whereas the variable set is formed of #rB's and ~oiB's The application of the DEA Model A requires a careful identification of inputs and outputs that is meaningful and feasible within the framework of the competitive environment of commercial banks

A complete D E A analysis involves the solution

of N such programs as formulated in (1)-(4) yielding N different (#~j, ~0ij ) weight sets In each program, the constraints are held the same while the ratio to be maximized is changed Such an analysis provides the following type of information for decision making purposes

1 Each bank being evaluated will have a value

E B, 0 < E B ~< 1, obtained from the DEA Model A indicating its efficiency level If E B < 1, the branch

is inefficient compared to 'best practice' units in the observation set ~ If E B = 1, this is a relatively 'best practice' branch and therefore is identified as an efficient one However, the branch so identified as an efficient one is not necessarily efficient in an absolute sense, it is simply not less efficient than other branches in the observation set ~

2 The DEA Model A will identify, from the viewpoint of a Base Branch B, the 'efficiency reference set' ~ B or 'efficient frontier' which is a

with E = 1 from the observation set ~ The Base Branch B is compared against the branches in ~B

to find the sources of its inefficiency, if any This allows a bank manager to locate and understand the nature of the existing inefficiencies by comparing h i s / h e r branch with a select subset of more efficient branches It therefore avoids the need to investigate all branches to understand the existing inefficiencies, and consequently helps allocate limited managerial resources to areas where efficiency improvements are most likely to be achieved

3 The D E A Model A hence produces information with which managerial measures (reducing the inputs used, or increasing the outputs produced) can be formulated to make an inefficient branch relatively efficient

These points will be more clearly illustrated when the application of the DEA Model A is discussed later in the text The reader is also

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referred to Sherman (1984a, b), Sherman and Gold

(1985), and Parkan (1987) for similar arguments

It is of great use, as will be seen later while

discussing the empirical results of this study, to

have the dual formulation of the DEA Model A

for formulating managerial measures to be taken

Using XBj's as the dual variables corresponding to

the constraints in (3), Sr~B and s ~ ' s to the con-

and Z a to the constraint in (2), we have the dual

formulation as follows:

r = l i = 1

subject to

N

X B ~ y - Y r B - sTB = 0,

j = l

N

E ~kBjXij -'b ZBXiB S~B = O,

J = l

i = 1 , 2 I,

(7)

(8)

XBj>~0, SrB+ >0,-/ S m- >/0 Vj, r, i,

Z B unconstrained in sign

The interpretation of the slack variables s+B

and S,B is as follows If the optimal s+B * > 0, then

it is possible to increase output r by s+B * without

altering any of the h Bj values and without violat-

ing any constraints Similarly, if s,~* > 0 then we

can reduce the use of input i from XiB to X m

S,~*, again without altering any of the ?~Bj values

and without violating any constraints The eco-

nomic interpretation of the optimal Z ~ , on the

other hand, is that the Base Branch B must use

less of each input by a quantity that is equal to

(1 - z ~ )x,~ + s,B*

in order to become efficient With this observa-

tion, the role of ~aj's becomes rather clear The

'Composite Branch', which is the efficient branch

that the Base Branch B would like to become by

reducing its input usages by quantities of

(1 - Z ~ )X,B + S,~*,

can be defined in terms of the optimal hBy s

More precisely, the 'Composite Branch' Pc is the

point that is given by

E x%pj,

j E J # ' B

where Pj is the point corresponding to the efficient branch j Then ~ j can be interpreted as the technical weight given to branch j in defining the

A final remark regarding the application of the DEA Model A as formulated above is that the efficiency thus identified (henceforth it will be termed as " t h e locally most favourable efficiency" since the reference set is determined by the Base

managerial measure based on the implications of such an efficiency index may not be sufficient to completely remove the inefficiency present A way

of partially avoiding this kind of overestimation is

to compare the efficiency of the Base Branch B also with the efficiency of the 'global leader', the bank branch which is identified as efficient by all

or almost all bank branches in the observation set Making 'the global leader' a member of the reference set forces the Base Branch B to compare itself with a better branch while formulating its managerial measures The DEA model that will yield 'the globally most favourable efficiency' can

be formulated as follows

DEA Model B

R

r = l

subject to

1

E iDiB : I,

i=l

E btrBYrj E WiBXij<~O

r = l i = 1

(lO)

for j = 1, 2 N,

(11)

E ~rBYrL E £OiBXiL = O, ( 1 2 )

r = l i = 1

where the subscript " L " denotes 'the global leader' The constraint in (12) is introduced simply

to force the Base Branch B to have ' t h e global leader' in its reference set To obtain a solution from the D E A Model B, one needs to identify 'the global leader' In this study, this is done by following the steps below:

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Step 1: Find the efficiency reference set for

each and every bank branch using the DEA Model

A yielding the most favourable efficiency

Step 2: Determine, for each and every bank

branch, the number of their appearances in the

efficiency reference sets

Step 3: Identify the bank having the highest

number of appearances in the efficiency reference

sets Suppose that is Bank Branch L Hence, the

constraint in (12)

In reality, we need both DEA models in order

to determine the corrective actions to be taken

more realistically since the Base Branch B is forced

to compare itself with 'the global leader' as well

In this empirical study, both of the models were

used in the performance evaluation of the bank

branches and in the formulation of managerial

measures

3 Banking sector in Turkey: A background

This section addresses itself to a short descrip-

tion of the banking sector in Turkey for the pur-

pose of providing a minimal background in order

to put later discussions in perspective

From the viewpoint of operating efficiency of

banks, it is perhaps best to discuss the policies

governing the banking sector in Turkey in two

periods:

(i) the period prior to the National New Eco-

nomic Policy introduced in January 1980, and

(ii) the period after January 1980

During the period prior to January 1980 the

commercial banks of oligopolistic nature had

hardly faced any competition in terms of collect-

ing funds and giving loans As a consequence of

this, they had acted almost in a monopolistic

manner in determining the interest rates to be

applied to credits and to deposits The typical

relationship between the interest rate I c charged to

credits, the interest rate I d paid on deposits and

the inflation rate I was almost always in the form

of ld < Ic < I The economic implications of this

relationship were, in summary, threefold:

1 There was not much incentive for an average

person to deposit h i s / h e r savings in the commer-

cial banks since I d < I Therefore private savings

were mostly invested in real estate, or in company

shares, or simply in gold In other words, private

savings were mostly channeled to construction

and industrial firms The private savings deposited

in the commercial banks were usually short term deposits to meet daily needs

2 There was great incentive for industrial firms

to borrow since the inflation rate was always considerably higher than the interest rate paid on loans; that is, I > I c Having revenue based on the inflation rate and financial cost based on a lower interest rate had only helped industrial firms improve their financial positions, without much need

to increase their capital It was common practice for any business-minded person to 'borrow and invest' in industrial activities This favourable position of the industrial firms was further rein- forced by the protectionist 'import-substitution' policies of the governments of different economic positions and by relatively large domestic demand for industrial products

3 The large difference I c - I d , compared with those in industrialized countries, secured rather handsome profits for the commercial banks in the country, and hence gave confidence, perhaps over- confidence, to the banking sector High profits were attributed, without feeling much need for a careful analysis, to the assumed skill of top level bank managers Not acknowledging the political- economic context in which these handsome profits were made did not help the commercial banks very much to improve their productivity

The new economic policies adopted in January

1980, which introduced the spirit of a free market economy and competition, have not only had a considerable impact on restructuring the national economy but also on the way business is con- ducted in the banking sector Like industrial firms, the existing traditional commercial banks have suddenly found themselves in fierce competition not only with foreign banks but also with thou- sands of local financial firms of different sizes These local financial firms, although many of them petitioned for bankruptcy shortly after coming into existence, have successfully competed against the traditional commercial banks by offering interest rates on deposits higher than the inflation rate, which was something that never happened in the recent economic history of Turkey The impact

of this on the banking sector can be summarized

as follows:

1 The traditional commercial banks had to offer competitive interest rates on savings accounts

in order to attract and maintain their clients

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against the new local financial firms This compe-

tition has increased the cost of funds for the banks

and financial firms

2 To maintain their usual level of profits, the

commercial banks had no alternative but to charge

higher interest rates to their industrial customers

which have been accustomed to use inexpensive

credits rather than their own financial resources

Faced with paying high interest rates on credits,

even higher than the inflation rate for the first

time, industrial firms have not only tried to reduce

their financing costs by decreasing credit requests

from the banks but also increased their capital by

issuing new shares to the public with very favoura-

ble payment plans, thus becoming serious compe-

titors of banks and financial firms in collecting

funds

3 The new economic policies seem to serve the

average person with savings rather well by offer-

ing several attractive alternatives for investment

Even the trend to invest in real estate has been

considerably reversed during this period in favour

of deposits The commercial banks, on the other

hand, seem to suffer, at least temporally, from the

new economic system, especially in maintaining

their accustomed level of profits since the rate of

increase for credit applications has dropped, thus

cutting down the revenue sources of commercial

banks

The points discussed above can also be ob-

served from the relevant statistics The annual

percentage increase in credit applications shows

first a sharp decline starting in 1981, from 66.6%

to 39.2%, and continues to decrease down to the

level of 29.4% in 1984 This is mainly due to the

reluctance of industrial firms to borrow money

from the commercial banks because of t h e high

interest rates charged on loans Having less than

usual credit applications has resulted in a profit

squeeze for the commercial banks The profit in-

crease rate in constant prices suddenly dropped

from 267% in 1980 down to 70% in 1981 Even

negative profit increase rates (meaning profit de-

creases in constant prices) were observed in 1982

and in 1983

In order to improve their weakened positions

the commercial banks have tried to make their

services accessible to customers even in remote

regions in the country by rapidly increasing the

number of their branches The commercial banks

increased their branches from 2862 in 1976 to

3351 in 1986, meaning at least 489 new branches

in a decade This has certainly contributed to increases in deposits, but at the cost of paying higher interest rates due to the competition and at the cost of investing in new branches Also real- ized during this period was the importance of operating efficiency of bank branches, an aspect constantly overlooked before

4 The field study

The Commercial Bank (henceforth simply "The Bank") for which this study was done is one of the major national banks operating in Turkey and employs around 9500 personnel in its 583 branches

of different sizes The executives of The Bank have distinguished themselves, through the years, as managers most receptive to new banking technol- ogy and management tools They have initiated many studies, especially after the introduction of the National New Economic Policy in January

1980, in order to improve the performance of the branches and provide high levels of service to their client The DEA study being reported here is one

of the studies initiated in that epoch

Before going into the discussion of the empirical study done, it may be most appropriate to comment on the nature of the previous applications of the DEA models Initially, DEA models

for-profit organisations such as schools (Bessent and Bessent, 1980, Bessent et al., 1982, Bessent et al., 1983), hospitals (Nunamaker, 1983, Banker, Conrad and Strauss, 1986, Sherman, 1984a, b), courts (Lewin, Morey and Cook, 1982), public projects and programs (Charnes, Cooper and Rhodes, 1981), the military (Bowlin, 1987), etc Through time, however, the application of DEA

organisations as well The most noticeable among these application studies are the ones reported by Byrnes, F~ire and Grosskopf (1984), Sherman and Gold (1985), Parkan (1987), and Byrnes and Fare (1987) In all these applications, the DEA models used were basically some versions of the type A given in (1)-(4) This study, on the other hand, employed both the DEA Model A and the DEA Model B in order to suggest more realistic measures by comparing the performance of the base branch with those of 'the local leaders' (DEA

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Model A) and 'the global leader' (DEA Model B)

Moreover, the possible relationship between

service efficiency and profitability of bank

branches was also investigated This was done by

considering different combinations of inputs and

outputs

The steps followed in conducting the field study

and their brief descriptions are given below

Step 1 Selection of Bank Branches for the Study:

It seems that the DEA models are most meaning-

ful when they are applied to observation sets of

units or organisations providing similar services

and using similar resources By the same argu-

ment, it makes little sense to compare very large

bank branches to very small ones since there will

be rather considerable differences in the services

rendered and the resources used The homogeneity

requirement was taken into consideration while

forming the observation set of this study The first

20 bank branches (all in Istanbul) having a rank-

ing score S between 61-80 were selected to form

the observation set ~ for this study The ranking

score Sj, 0 ~< Sj ~< 100, of bank branch j is given

by

where

=

W

the points assigned to bank branch j using

a predetermined function mapping the

amount of money deposited in the bank

branch on a scale of 0-100,

amount of loans given to clients in the bank

branch on a scale of 0-100,

amount of foreign exchange transactions in

the bank branch on a scale of 0-100

amount of profit made in the branch on a

scale of 0-100,

a predetermined function mapping the num-

ber of personnel in the bank branch on a

scale of 0-100,

the positive weights, the sum of which is

equal to unity, given to the above factors

Step 2 Identification of Input and Output Sets:

As mentioned earlier this study addressed itself not only to assess the service efficiency of bank branches but also to analyse their profitability Therefore, two sets of inputs and outputs were needed; one set for service efficiency assessment, and one for profitability analysis

consisted of five elements:

x a = the number of personnel, x2 = the n u m b e r of on-fine terminals, x3 = the n u m b e r of commercial accounts, x4 = the n u m b e r of saving accounts,

x 5 = the number of credit applications

The first two items, usually under the direct control of bank managers in the short run as well

as in the long run, are widely used factors as inputs in most D E A applications in banking sector The last three items, which are usually in- fluenced in the long run, are also frequently used

reflect the steady state market conditions which have been established through years In other words, the equilibrium state achieved (or the clien- tal infrastructure developed) i n the market as a result of the previous efforts and achievements in obtaining and maintaining clients was considered

to be the market structure or environment pro- vided to the bank branch, and hence an input to the current operations

ment, although 11 different outputs were initially identified, a set of only four outputs was considered; namely,

y~ = the amount of time spent on general service transactions (accounting, control, information, transfers, payments),

Y2 = the amount of time spent on credit transactions (contracts, guarantees, credit and risk related procedures),

Y3 = the amount of time spent on deposit transactions (commercial accounts, saving accounts), Y4 = the amount of time spent on foreign exchange transactions

Observe that the outputs above are measured in

time units Traditionally, it is the number of transactions that is used in DEA applications There were two reasons for quantifying outputs in time

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units First, the results of this D E A analysis were

to be c o m p a r e d with those obtained from The

Performance Evaluation Model (referred to as

P E M henceforth), a model already in use in The

Bank and its outputs are measured in time units

Second, it was observed that there is a strong

relationship between the annual n u m b e r of trans-

actions of a particular type and the annual total

time spent on these transactions

Given the fact that the commercial banks are in

business also for profit, it is quite legitimate to ask

whether achieving a high level of service efficiency

implies a high level of profitability as well To

investigate this, the D E A Models A and B were

used, this time with a different set of inputs and

itability assessment consisted of four main items:

x I = personnel expenses,

x 2 = administrative expenses,

x 3 = depreciation,

x 4 = interests paid on deposits

Note that the inputs above correspond to major

cost items of b a n k operations The output set of

profitability assessment, on the other hand, in-

cluded only two items which accounted for a

sufficiently large part of total income of a b a n k

branch; namely,

y~ = interests earned on loans,

Y2 = non-interest income

With the above sets of inputs and outputs for

profitability assessment, it is clear that the ratio

T a b l e 1

I n p u t - o u t p u t c o m b i n a t i o n s f o r s e r v i c e e f f i c i e n c y a s s e s s m e n t

I n p u t s a n d o u t p u t s C o m b i n a t i o n s a

(1) (2) (3) (4) (5)

x l = n u m b e r o f p e r s o n n e l + + + + +

x 2 = n u m b e r o f t e r m i n a l s + + + + +

x 3 = n u m b e r o f c o m m e r c i a l a c c o u n t s + + -

x 4 = n u m b e r o f s a v i n g a c c o u n t s + + -

x 5 = n u m b e r o f c r e d i t a p p l i c a t i o n s + + + + +

x 6 = x 3 + x 4 + + +

y~ = t i m e o n g e n e r a l s e r v i c e s + +

Y2 = t i m e o n c r e d i t s + + +

Y3 = t i m e o n d e p o s i t s + + +

Y4 = t i m e o n f o r e i g n e x c h a n g e + +

a + ( _ ) i m p l i e s t h e i n c l u s i o n ( e x c l u s i o n ) o f t h e v a r i a b l e

T a b l e 2

I n p u t - o u t p u t c o m b i n a t i o n s f o r p r o f i t a b i l i t y a s s e s s m e n t

I n p u t s a n d o u t p u t s C o m b i n a t i o n s a

( 1 ) (2) (3) x~ = p e r s o n n e l e x p e n s e s + + +

x 2 = a d m i n i s t r a t i v e e x p e n s e s + + -

x 3 = d e p r e c i a t i o n + + -

x 4 = i n t e r e s t s p a i d + + +

Yl = i n t e r e s t s e a r n e d + - + Y2 = n o n - i n t e r e s t i n c o m e + - +

a + ( _ ) i m p l i e s t h e i n c l u s i o n ( e x c l u s i o n ) o f t h e v a r i a b l e

appearing in the objective functions of D E A models is nothing but the ratio of weighted sum of revenues to weighted sum of expenses, hence an index of profitability

Step 3 Calculation of Efficiencies: Two series of calculations were made, one for service efficiency and one for profitability In each case, different combinations of inputs and outputs were used in order to investigate their possible impact on efficiency index The i n p u t - o u t p u t combinations that were considered are given in Tables 1 and 2 The different combinations of i n p u t s - o u t p u t s allowed us to investigate how much the efficient frontiers differed from one another This was needed to have a reasonable level of confidence in the managerial suggestions to be made later based

on these results

Step 4 Identification of the Sources of Inef- ficiencies: Based on the efficiency calculations and efficiency reference sets, the weaknesses of the inefficient b a n k branches were identified, albeit in general terms This was done with respect to service efficiency and profitability

Step 5 Formulation of Suggestions: As a final step of the study, a set of managerial suggestions, thought to be most likely to improve the performance of the inefficient bank branches, was formulated

5 Empirical results

This section includes not only a discussion and interpretation of the computational results but also some observations and c o m m e n t s on the methodology employed in this empirical study

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First, we shall present the general observations

and findings and then the managerial implications

of the computational results

5.1 General observations and findings

The DEA models used in this study were in-

strumental in reaching the following conclusions:

1 Although there are suggestions in the perti-

nent literature as to which i n p u t - o u t p u t combina-

tions should preferably be used in measuring the

operating efficiency of bank branches, it is not

very evident that these are the ones always to be

used regardless of the competitive environment

and organisational nature of bank branches In

this study, therefore, different i n p u t - o u t p u t com-

binations were considered to find out the most

meaningful one From Table 3, it can be observed

that Combination (5) seems to have the capacity

to better discriminate the bank branches accord-

ing to service efficiency assessment Observe that

only 4 efficient bank branches were identified with

Combination (5) opposed to 11, 10, 9, and 5

efficient bank branches with the Combinations

(1), (2), (3), and (4), respectively Having 10-11

efficient bank branches, as in the cases of Combi-

nations (1) and (2), in a set of 20 members is not

of much help in comparing and contrasting the efficiencies of the bank branches since almost every bank branch has a perfect or near perfect efficiency score As a result of this observation, Combination (5) was chosen as the i n p u t - o u t p u t combination to analyze the service efficiency of bank branches A similar approach was also used

in determining the i n p u t - o u t p u t combination for profitability analysis and Combination (1) was chosen for this purpose

2 As can be easily observed from Table 6, according to service efficiency assessment the bank branches 12, 16, 17 and 20 consistently appear in the efficiency reference sets, implying that all the branches seem to have agreed that these four branches are the efficient ones Similarly, the most efficient branches according to profitability assessment are 11, 12, 16 and 20

3 As mentioned earlier both DEA Model A and DEA Model B were used in this study For service efficiency assessment Model B was based

on Bank Branch 16, 'the global leader', since it has appeared 17 times in the efficient reference sets, implying that 17 bank branches out of 20 identified it as efficient for service efficiency (see

Table 3

The D E A efficiency results

Bank

branches

Service efficiency combinations

Profitability combinations

Trang 10

Table 6) As for profitability, Bank Branch 11,

which has appeared 17 times in the efficiency

reference sets, was chosen as 'the global leader'

for the DEA Model B It has been observed that

Model B, indicating that the Base Branch B was

quite realistic and not favouring itself very much

in estimating the weights to be assigned to inputs

B

distinction between DEA Model A and DEA

Model B Although in this particular empirical

study two DEA models are not, for practical pur-

poses, distinguishable from one another, this might

not be the case in all real life settings, and there-

fore it is always wise to consider the DEA Model

B in applications in order to find out whether one

has the tendency to overstate its own efficiency

compared to the one of the ' t h e global leader'

This kind of precaution will only help to for-

mulate more realistic managerial measures

4 It has been also observed that there seems to

be a close relationship between the service ef-

ficiency and profitability of a bank branch In

general, a bank branch realizing lower profit may

not be necessarily performing less efficiently than

the ones with high profits In other words, the

bank branches may not be very efficient in trans-

action activities but may be quite profitable, or

vice versa The results of this study however show

that the service-efficient branches are also profit-

able Having such a relation between service ef-

ficiency and profitability has increased the confi-

dence of The Bank managers in the DEA models

used

5.2 Computational results

In the light of the general observations and

comments made above, we will present the com-

putational results obtained from the DEA Model

A using Combination (5) (inputs xl, x2, x 5 and

x 6 and output Y6) for service efficiency, and Com-

bination (1) (inputs x 1, x 2, x 5 and x 6, and output

Y6) for service efficiency, and Combination (1)

(inputs Xl, x 2, x 3, x 4 and outputs Yl, Y2) for

profitability and their managerial implications

The analysis of the findings will be presented in two groups:

(i) global analysis, (ii) detailed analysis

(i) Global analysis: From Table 3 above it is clear that Bank Branches 12, 16, 17, and 20 are the service-efficient ones whereas Bank Branches 19,

2, 9, and 18 are the most inefficient four A comparison of the characteristics of the group of efficient branches with those of most inefficient ones has revealed the following:

1 The efficient branches turned out to be relatively new compared to the inefficient ones The average age of an efficient branch is 15 years, compared with 23 years in the case of inefficient ones This is perhaps partially due to the dynamics

of the national economy in general and to the high rate of urbanization process in particular, which imply the demand for banking services is not only increasing but also shifting from one location to another The latter forces commercial banks to open new branches in newly urbanized sections of the cities and towns to increase or maintain their market shares

2 The efficient branches employ, on the average, less personnel than the inefficient ones, 20 personnel opposed to 25.5 This is also true for the average number of on-line terminals used, 6.25 against 7.25 in favour of the efficient branches

3 In terms of the factors shaping the steady state market conditions (the number of saving and commercial accounts, and the number of credit applications), an efficient branch, on the average, has less accounts (3714) compared to an inefficient one (5962) This result is quite normal since the efficient branches are relatively new and therefore they have not been in the market long enough

to capture as many accounts as the inefficient ones have, which are relatively older Although the average number of accounts seems to be lower for

an efficient branch (3714 vs 5962), the number of transactions per account, on the other hand, is much higher (25.3 vs 15.2) Even though efficient and inefficient branches have approximately the same level of deposit in monetary units, the average amount of deposits per account is 1.80 times higher in the efficient branches In other words, the efficient branches have accounts which are 'active', meaning there is a spatial shift in demand for banking services This in fact is in agreement with the above observation regarding economic

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