response of bank officials on the impact of...

Chapter VIII

RESPONSE OF BANK OFFICIALS ON THE IMPACT OF REFORMATION ON BANKING

SECTOR IN KERALA

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CHAPTER VIII

RESPONSE OF BANK OFFICIAL’S ON THE IMPACT OF REFORMATION ON BANKING

SECTOR IN KERALA

There has been a change in the economic policy of India since the

beginning of the 1990s, when she adopted the liberalization, privatization and

globalization model of development. The financial sector reforms in India

comprise two phases. The first phase of reforms was based on the

recommendations of the first Narasimham committee in 1991. The major

recommendations can be classified into (i) Improving the financial soundness

of banks; (ii) Strengthening of the institutional frame work; (iii) Strengthening

of supervisory mechanism and (iv) Modifying the policy frame work which

included reduction in pre-emption of resumes and interest rate deregulation.

The second phase of reforms was based on the recommendations of the

second Narasimham committee in 1998. The main focus of this committee

was to suggest measures to strengthen the banking sector to make them more

competitive in the changing international scenario.

The impact of reformation may be measured by the operational

efficiency, allocation efficiency and financial efficiency of the commercial

banks. The above said efficiencies are measured with the help the financial

facts and the relevant-financial ratios. One of the important measurements of

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such impact of reformation is the banks officials’reponse on the reformation.

It is highly imperative to reveal the opinion of the bank officials on the

reformation and its consequences since they are the persons who are facing

the impact of reformation in their practical life. Hence, this study focuses on

measuring the attitude of bank officials on the reformation.

For selecting the sample group of bank officials, the banks are divided

into two i.e. public and private sector banks. The Private sector banks have

again classified into Old Private Sector Banks (OPRSBs) and New Generation

Private Sector Banks (NGPSBs). So banks are grouped into three as PUSBs,

OPRSBs and NGPSBs.

For this study ten officer grade officials each from public sector, old

private sector and New Generation Private Sector Banks have been selected

from each of the 14 districts in Kerala. So thirty officials from each district

totaling of 420 officials for the whole state of Kerala has been studied.

The profile of the officials is imperative to exhibit the back ground of

the officials. So the study includes the profile of bank officials and their

attitude on the reformation. Even though the profile variables are too many,

the present study confine these variables to sex, age, level of education, years

of experience, number of banks worked, number of departments worked,

present designation, monthly income, number of training programmes

attended and banking orientation among the officials. The sex wise bank each

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distribution of officials in public sector banks (PUSBs), Old Private sector

banks (OPRSBs) and New Generation Private Sector Banks have been

analyzed and presented in Table 8.1.

TABLE 8.1

Sex wise distribution of bank officials selected as sample.

SL. No. Sex Number of respondents in

Total PUSBs OPRSBs NGPRSBs

1 Male 111 119 127 357 2 Female 29 21 13 63 Total 140 140 140 420

The important sex proportion among the bank officials is male which

constitute 85.00 percent to the total. In all three groups of banks, the

important sex among the bank officials is male which constitutes 79.28, 85.00

and 90.71 percent to the total officials in public, old private and New

Generation Private Sector Banks respectively. The analysis refers the

dominance of the male bank officials in the present study.

Age among the officials:

The age of the officials is one of the important profiles of the officials.

Since the age of the officials shows their maturity and experience in banking,

it is included as one of the profile variables. In general, the aged officials may

have more knowledge and experience in banking as well as the idea on impact

of reformation in banking compared to youngsters. At the same time the

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young officials may have more idea on globalization and the impact of

globalization in banking. Hence, the study includes the age of the officials as

the profile of officials. The age among the officials is confined to less than 40

years; 40 to 45; 46 to 50; 51 to 55 and above 55 years. The distribution of

officials on the basis of their age is presented in Table 8.2.

TABLE 8.2

Age wise distribution of selected bank officials

Sl. No. Age Number of respondents in


1 Less than 40 19 15 19 53 2 40-45 21 32 41 94 3 46-50 41 45 38 124 4 51-55 31 29 25 85 5 Above 55 28 19 17 64 Total 140 140 140 420

In total, a maximum of 29.52 percent of the officials are in the age

group of 46 to 50 years which is followed by 22.38 percent of the officials

with the age group of 40 to 45 years. The number of officials with the age

group of above 51 years constitutes 15.24 percent to the total. The most

important age group among the officials in PUSBs is 46 to 50 years which

constitutes 29.28 percent to its total. In OPRSBs, it is also 46 to 50 years

which constitutes 32.14 percent to its total. In the case of NGPRSBs, it is 40-

45 years which constitutes 29.28 to its total. The analysis reveals that the

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average age among the officials in NGPRSBs is less than among officials in

OPRSBs and PUSBs.

Level of education among the officials:-

The level of education among the officials reveals the educational

standard among the officials. Since the educational level among the officials

may provide more knowledge on the reformation and its consequences in

banking industry, is included as one of the profile variables. The level of

education among the officials is classified into under graduation, post

graduation, under graduation with CAIIB, post graduation with CAIIB and

other which includes professional and technical education. The officials with

different educations background is shown in Table 8.3

TABLE 8.3

Level of education among the selected bank officials

Sl. No. Level of education

Number of respondents in Total

PUSBs OPRSBs NGPRSB 1 Under Graduation 29 17 19 65 2 Post Graduation 26 32 29 87 3 Under Graduation with CAIIB 39 33 35 107 4 Post Graduation with CAIIB 27 36 40 103 5 Others 19 22 17 58 Total 140 140 140 420

The important level of education among the officials is under

graduation with CAIIB and post graduation with CAIIB which constitute

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25.48 and 24.52 percent to the total respectively. The most important level of

education among the officials in PUSBs is under graduation with CAIIB

which alone constitutes 27.86 percent to its total whereas in OPRSBs, it is

post graduation with CAIIB which constitutes 25.71 percent to its total. In the

case of NGPRSBs, it is post graduation with CAIIB which constitutes 28.57

percent to its total. The analysis refers the higher level of education is

identified among the bank officials in NGPRSBs and OPRSBs compared to

PUSBs.

Years of experience among the officials:-

The years of experience indicates the number of years the officials

have gathered the experience in the banking industry. The years of experience

among the officials may provide adequate knowledge to predict the trends in

the banking. Hence, it is included as one of the profile variables. The years of

experience among the bank officials is confined to less than 15 years, 15 to

20; 21 to 25; 26 to 30 and above 30 years. The distribution of officials on the

basis of their experience is exhibited in Table 8.4.

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TABLE 8.4

Years of experience among the selected bank officials

Sl. No.

Years of experience in Years


PUSBs OPRSBs NGPRSBs 1 Less than 15 18 23 68 139 2 15-20 29 31 52 123 3 21-25 29 38 7 73 4 26-30 36 27 6 47 5 Above 30 28 21 7 38 Total 140 140 140 420

The dominant years of experience among the officials are less than 15

years which constitutes 33.09 percent to the total. It is followed by 15 to 20

years which constitutes 29.29 percent to the total. The most important years of

experience among the officials in PUSBs are 26 to 30 years which constitutes

25.71 percent to its total. In the case of OPRSBs, it is 21 to 25 years which

constitutes 27.14 percent to its total whereas in the case of NGPRSBs it is less

than 15 years with the percent age of 48.57 percent to the total. The analysis

reveals that the officials in PUSBs have more experience than the officials in

other two groups of banks.

Number of branches worked so far:-

It indicates the number of branches worked so far by the officials in his

career. The higher number of branches experienced by the officials may

provide more knowledge and experience among the officials. Hence, they

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may provide a correct picture on the impact of reformation of banking in

India. The number of branches worked so far by the respondent of this study

is classified into less than 5 branches, 5 to 8; 9 to 12; 13 to 16; and above 16

branches. The distribution of officials on the basis of number of branches

worked so far is given in Table 8.5.

TABLE 8.5

Number of branches worked by the selected bank officials

Sl. No.

Number of branches


PUSBs OPRSBs NGPRSBs 1 Less than 5 7 34 39 80 2 5-8 29 42 48 119 3 9-12 66 39 48 153 4 13-16 27 18 5 50 5 Above 16 11 7 18 Total 140 140 140 420

The maximum number of branches worked so far among the officials

is 9 to 12 branches which constitutes 36.43 percent to the total. It is followed

by 5 to 8 branches with the percentage of 28.33 percent to the total. The

number of officials with the experience with less than 5 branches constitutes

19.05 percent to the total. The maximum number of branches experienced

among the officials in PUSBs and OPRSBs is 9 to 12 and 5 to 8 branches

respectively which constitute 47.14 and 30.00 percent to its respective total.

In the case of NGPRSBs, it is 5 to 8 years which constitutes 34.28 percent to

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its total. It reveals that the officials in PUSBs have experience with more

branches compared to others.

Number of departments worked so far:-

There are many departments in a particular branch of bank. The

officials may have gathered experience at various departments in different

branches he/she has worked. Since the number of departments worked so far

by the officials may provide more exposure and knowledge on the banking. It

is included as one of the profile variables. The number of departments worked

so far among the bank officials is confined to less than 3; three, four, five and

above five. The distribution of officials on the basis of the number of

departments worked so far is illustrated in Table 8.6.

TABLE 8.6

Number of departments worked by selected bank officials

Sl. No. Number of Departments Number of respondents in


1 Less than 3 21 23 19 63 2 Three 25 36 23 84 3 Four 32 29 36 97 4 Five 39 33 35 107 5 Above five 23 19 27 69 Total 140 140 140 420

The maximum number of departments worked so far among the

officials is five which constitutes 25.48 percent to the total. The other two are

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four and three departments which constitutes 23.09 and 20.00 percent to the

total respectively. The maximum number of departments worked by the

officials in PUSBs and OPRSBs are five and three which constitute 27.85 and

25.71 percent to its total respectively. In the case of NGPRSBs, it is four

which constitutes 25.71 percent to its total. It infers that the officials in

PUSBs worked in more number of departments compared to the officials

worked in other two groups of banks.

Designation among the officials:-

The present study focuses the officials working in banks. Since the

bank officers may have more knowledge about reforms than other bank

employees, it has focused on the attitude of officiers only. The officials

included in this study are classified into manager, Assistant manager and

probationary officer. The present designation among the bank officials is

presented in Table 8.7.

TABLE 8.7

Present designation of the selected bank officials

Sl. No. Present designation


PUSBs OPRSBs NGPRSBs 1 Manager 73 86 88 247 2 Assistant Manager 44 36 31 111 3 Probationary officer 23 18 21 62 Total 140 140 140 420

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The important designation among the bank officials are manager and

Assistant manager which constitute 58.81 and 26.43 percent to the total

respectively. The most important present designation among the officials in

all three groups of banks is in the cadre of manager which constitutes 52.14,

61.42 and 62.86 percent to its total in PUSBs, OPRSBs and NGPRSBs

respectively. The number of probationary officers constitutes 14.76 percent to

the total.

Monthly income among the officials:-

The monthly income among the officials indicates the total income

earned by the bank officials per month. Since the monthly income have its

own influence on the attitude of the officials towards reformation, it is

includes as one of the profile variable. The monthly income among the

officials is confined to less than Rs. 25,000; Rs. 25,000 to 27,000; Rs.

27,0001 to 29,000; Rs. 29,001 to 31,000 and above Rs. 31,000. The

distribution of officials according to their monthly income is illustrated in

Table 8.8.

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TABLE 8.8

Monthly income among the selected bank officials

Sl. No.

Monthly income (Rs.)



The important monthly income among the officials is above Rs. 31000

and Rs. 29001 to 31000 which constitute 30.95 and 29.76 percent to the total

respectively. The number of officials with a monthly income of less than Rs.

25000 constitutes 7.62 percent to the total. The most important monthly

income of the officials is PUSBs is Rs. 29001 to 31000 which constitutes

35.00 percent to its total whereas in the case of OPRSBs, it is Rs. 29001 to

31000 which constitutes 37.14 percent to its total. In the case of NGPRSBs, it

is above Rs. 31000 which constitutes 32.86 percent to its total.

Number of training programmes attended.

The training programmes, seminars, workshops etc. may provide more

knowledge, exposure and training on various aspects in banking. The higher

number of training programmes attended by the officials may have its own

influence on their attitude towards the reformation in banking industry. Since,

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the number of training programmes attended by the bank officials is included

as one of the profile variables. The number of training programmes attended

so far is confined to less than 5, 5 to 10, 11 to 15, 16 to 20 and above 20. The

number of training programmes attended by the bank officials is illustrated in

Table 8.9.

TABLE 8.9

Number of training programmes attended by the selected bank officials

Sl. No.

Number of training programmes



The maximum number of training programmes attended by officials is

11 to 15 and 5 to 10 which constitute 26.19 and 20.24 percent to the total

respectively. The number of officials attended above 20 training programmes

constitutes 20.00 percent to the total. The number of officials attended les

than five training programmes constitutes 14.52 percent to the total. The most

number of training programmes attended by the officials in PUSBs and

PRSBs is 11 to 15 programmes which constitute 25.71 and 30.71 percent to

its total respectively. In case of NGPRSBs, it is above 20 which constitute

26.43 percent to its total. The analysis infers that the number of training

programmes attended by the officials in NGPRSBs is above 20 levels which

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are higher than the number of training programmes attended by the officials in

PUSBs and OPRSBs.

Banking orientation among the bank officials:-

The banking orientation represents the level of understanding,

knowledge and attitude towards the banking industry among the bank

officials. The banking orientation among the officials is measured with the

help of some related statements. The officials are asked to rate these statement

at five point scale according to their order of perception. The assigned marks

on these scales are from 5 to 1 respectively. With the help of the mean score

obtained by the officials from these statements, their level of banking

orientation is classified into excellent, good, moderate, low and very low. The

distribution of officials on the basis of their banking orientation is shown in

Table 8.10.

TABLE 8.10

Banking orientation among the bank selected bank officials

Sl. No. Level of banking

orientation


PUSBs OPRSBs NGPRSBs

1 Excellent 17 29 32 78 2 Good 29 21 24 74 3 Moderate 36 43 39 118 4 Low 36 29 21 86 5 Very low 22 18 24 64 Total 140 140 140 420

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The important banking orientation among the officials is moderate

which constitute 28.09 percent to the total. It is followed by low and excellent

which constitute 20.47 and 18.57 percent to the total respectively. The

number of officials with very low level of banking orientation constitutes

15.24 percent to the total. The most important level of banking orientation

among the officials in all three groups of banks is moderate which constitute

25.71, 30.71 and 27.86 percent to its total respectively.

Bank official’s response on the impact of reformation.

The bank officials response on the impact of reformation on banking is

measured with the help of attitude analysis. In total, 60 statements related to

various reform measures implemented in banking have been generated with

the help of reviews and views of experts. Both negative and positive

statements have been generated to avoid the biased view on the impact. The

officials are asked to rate these 60 statements at five point scales from ‘highly

agree’ to ‘highly disagree’. The marks assigned on the above scales on the

positive statements are from 5 to 1 respectively. Whereas in the case of

negative statements, the assigned marks are from 1 to 5 respectively. The

marks assigned by the officials on these 60 statements have been included for

measuring their response on the impact of reformation in banking.

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Measurement of bank officials response on reformation:-

The response of officials on reformation is analyzed with the help of

factor analysis. The score on 60 statements related to the impact of reforms on

banking sector have been included for the factor analysis. Initially, the

validity of data for factor analysis has been conducted with the help of Kaiser-

Meyer-Ohcin measure of sampling adequacy and Bartletts Test of Sphericity.

The above said two measures namely KMO and chi-square value satisfy the

validity of data for factor analysis since the KMO measure is greater than 0.5

and the chi-square value is significant at 5 percent level. Out of 60 statements

included for the factor analysis, 17 statements have been deleted because of

their factor loadings are lesser than 0.4 or a higher factor loading associated

with more than one factors. The remaining 43 statements are summated into

nine factors (impacts variables). The nine important impacts with the Eigen

value and percent of variation explained by these important impacts are

shown in Table 8.11.

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TABLE 8.11

Important impact variables of reformation

Sl. No. Important impacts

Number of statements involved in

Eigen value

Percent of variation explained

1 Profitability 6 5.1493 17.18 2 Recovery of debts 7 4.3021 16.32 3 General banking activities 8 3.9406 14.08 4 Service quality 6 3.0117 11.17 5 Portfolio Quality 4 2.9339 9.36 6 Operative efficiency 4 2.7082 8.44 7 Liquidity 3 2.1609 7.21 8 Competitive pressure 3 1.5544 6.32 9 Investments 2 1.0339 4.86

KMO measures of sampling Adequacy: 0.7682

Bartletts Test of Sphericity

Chi-square value: 93.0473*

* Significant at five percent level.

The narrated important impact variables of reformations are

profitability, recovery of debts, general banking activities, service qualities,

portfolio qualities, operative efficiency, liquidity, competitive pressure and

investments. The above said 9 important impacts explain the impact of

reformation of banking to the extent of 94.94 percent. The most important

impact is profitability since its Eigen value and the percent of variation

explained are 5.1493 and 17.18 percent respectively. It infers that the

profitability impact explain the impact of reformation of banking sector to the

extent of 17.18 percent. The next two important impacts are recovery of debts

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and general activity with the Eigen value of 4.3021 and 3.9406 respectively.

The percent of variation explained by the above said two important impacts

are 16.32 and 14.08 percent respectively. The other important impacts are

service quality and portfolio quality with the Eigen value of 3.0117 and

2.9339 respectively. The percent of variation explained by the above two

impacts are 11.17 and 9.36 percent respectively. The factor analysis resulted

in nine important impact variables which are the basis for further analysis.

Factor loading of the items in profitability:-

The factor analysis identifies six statements (statements related to

impact of reformation) which are included in the profitability criteria with the

reliability coefficient of 0.8189. It reveals that the six statements included in

profitability, explain the profitability to the extent of 81.89 percent. The

statements included in the profitability impact variable and its factor loading

associated with the above said profitability impact is shown in Table 8.12.

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TABLE 8.12

Factor loading of items in profitability

Sl. No.

Statements in profitability Factor loading

Reliability coefficient

1. Improvement in the financial performance after reforms 0.9086 0.8189

2. De-regulation of interest rates increased the bank’s profitability 0.8604

3. Investments in other sectors increased the rate of profitability 0.8143

4. Reduction in primary sector advances lead to concentrate on other profit making areas

0.7605

5. Elimination of directed credit policy will improve the profitability 0.6334

6. Reforms on asset classification, provisioning and interest recognition increased profits.

0.5811

The factor loadings are explaining correlation between the statements

included in profitability variable and profitability. The important items

included in the profitability are improvement in the financial performance

after reforms, de-regulation of interest rate increased the banks profitability

and investments in other sectors increased the rate of profitability since their

respective factor loadings are 0.9086, 0.8604 and 0.8143.

Factor loading of items in recovery of debts:-

The statements related to recovery of debts are narrated into one factor

by the factor analysis since its factor loadings are higher in the recovery factor

compared to other factors. In total, seven statements are clustered into

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recovery factor with the reliability coefficient of 0.8509. It infers that the

included statements on recovery of debts explain the items in recovery to the

extent of 85.09 percent. The factor loading of the items in recovery of debts is

presented in Table 8.13.

TABLE 8.13

Factor loading of items in recovery of debts

Sl. No. Statements in recovery of debts Factor

loading Reliability coefficient

1. Reduction in non performing assets after reforms 0.9518 0.8509

2. Debt recovery tribunals are of great help to banks 0.8567

3. Freedom to recover the debts improved 0.8108

4. Reforms acted as a pillar of confidence among public 0.7664

5. Higher post-credit supervision 0.7228

6. Bank gives lesser priority to agriculture, small business after reforms

0.6904

7. Decline in political and administrative interference in recovery of advances 0.5909

The higher factor loadings are identified in the case of reduction in non

performing assets, debt recovery tribunals are of great help to banks and

freedom to recover the debts is improved since its factor loadings are 0.9518,

0.8567 and 0.8108 respectively. It infers that the above narrated statements

are highly correlated with the recovery factor.

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Factor loadings of items in the general activity variable:-

The items related to general activity of banks is clustered into one

factor namely ‘Activity Impact’. It consists of 8 items with the reliability

coefficient of 0.8614. This shows that the included 8 statements in the

activity impact explains the activity variable to the extent of 86.14 percent.

The factor loading of the items included in the activity factor is illustrated in

the Table 8.14.

TABLE 8.14

Factor loading of items in the general activity

Sl. No.

Statements in general activities of banks

Factor loading


1. Improvement in the growth of deposits 0.8682 0.8614 2. Increase in lending to corporate sector 0.8441

3. Deregulation of interest rates speed up the mobilization of deposits 0.8017

4. Increase in credit availability to the public 0.7809

5. Directed credit programmes lead to decrease in profitable lending 0.7434

6. Increase in credit deposit ratio 0.7028 7. Lending is made more accountable 0.6906

8. Non insistence on collateral security speed up the lending function of banks 0.5892

The highly correlated items in the activity impacts are improvements in

the growth of deposits, increase in lending to corporate sector and

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deregulation of interest rates speed up the mobilization of deposits since its

factor loadings are 0.8682, 0.8441 and 0.8017 respectively.

Factor loading of items in the service quality variable:-

The statements related to the service quality of the banks are clustered

into one factor by the factor analysis. In total, six statements are included in

the service quality factor. The reliability coefficient of the factor reveals that

the included items in the service quality criteria of the banks explain the

service quality factor to the extent of 73.44 percent. The items included in the

service quality factor and its factor loadings are summarized in Table 8.15

TABLE 8.15

Factor loading of items in the service quality

Sl. No. Items in service quality Factor


1. Improvement in the reliability of banks after reforms 0.9033 0.7344

2. Increase in the healthy competitions among the banks 0.8439

3. Increase in morale of bankers 0.8108

4. Increase in customer service facilities 0.6917

5. Increase in work culture among the staffs 0.6024

6. Modern technology improved service quality 0.5594

The first three items included in the service quality factor are

Improvement in the reliability of banks, increase in the healthy competitions

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among the banks and increase in morale of bankers since their factor loadings

are 0.9033, 0.8439 and 0.8108 respectively.

Factor loading of items in portfolio quality:-

The statements related to the portfolio quality of banks are grouped

into one factor namely portfolio quality by the factor analysis. This portfolio

quality factor consists of 4 items with the reliability coefficient of 0.7608. It

infers that the items included in the portfolio quality explain the portfolio

quality impacts to the extent of 76.08 percent. The factor loading of the items

included in portfolio quality is shown in Table 8.16.

TABLE 8.16

Factor loading of items in portfolio quality

Sl. No. Items in portfolio quality Factor


1. Improvement in portfolio quality 0.8917 0.7608

2. Directed credit programmes adversely affect the loan portfolio 0.7233

3. Desire to attain credit targets has badly affected in qualitative aspects of lending

0.6918

4. Autonomy of banks increased the quality of lending 0.5249

The factor loading of the items in each factor indicates the correlation

between the items and the factor. The higher correlation between the

statements and the portfolio variable is identified in the case of improvement

in portfolio quality, directed credit programmes adversely affected the loan

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portfolio and desire to attain credit targets has badly affected in qualitative

aspects of lending since its factor loadings are 0.8917, 0.7233 and 0.6918

respectively.

Factor loading of the items in operative efficiency:-

The item related to operative efficiency of the banks are clustered into

one factor since its factor loadings are identified as higher in operative

efficiency factor compared to other factors. In total, four statements are

included in the operative efficiency factor with the reliability coefficient of

0.7802. It infers that the items include in the operative efficiency factor

explain the operative efficiency to the extent of 78.02 percent. The factor

loading of the items included in this factor is given in Table 8.17.

TABLE 8.17

Factor loading of the items in operative efficiency

Sl. No. Items in operative efficiency Factor


1. Improvement in the productivity of banks after reforms 0.9337 0.7802

2. Growth in number of commercial banks after reforms 0.8608

3. Latest technology improved the performance of banks 0.8173

4. Emerging operational indicators 0.6246

The important items included in operative efficiency impact are

improvement in the productivity of banks, growth in number of commercial

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banks and latest technology improved the performance since its respective

factor loadings are 0.9337, 0.8608 and 0.8173.

Factor loading of the items in liquidity: -

The statements related to the liquidity of the banks are clustered into

one of the important impacts by the factor analysis. It shows the improvement

of liquidity of the banks after reformation. In total, 3 items are included in the

liquidity factor with the reliability coefficient of 0.7309. It reveals that the

items included in the liquidity factor explain the liquidity to the extent of

73.09 percent. The factor loading of the items included in liquidity is given in

Table 8.18.

TABLE 8.18

Factor loading of the items in liquidity

Sl. No. Items in liquidity Factor


1. Reduction in SLR & CRR increases the lending capacity of banks 0.8211 .7309

2. Reform measures increased the funds for profitable lending 0.7096

3. Optimum allocation of resources 0.6833

The first two items included in the liquidity factor are reduction in SLR

and CRR increase the lending capacity of banks and increase the funds for

lending since its factor loadings are 0.8211 and 0.7096 respectively.

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Factor loading of the items in competitive pressure: -

After reformation, the competitive pressures among the banks are

increasing. In order to measure such impact, some of the statements related to

competitive pressure have been included in the factor analysis. The factor

analysis identify that three items related to competitive pressure is clustered

into one factor with the reliability coefficient of 0.7449. It infers that the items

included items included in competitive pressure explain the competitive

pressure to the extent of 74.19 percent. The factor loading of the items

included in competitive pressure is shown in Table 8.19.

TABLE 8.19

Factor loading of the items in competitive pressure

Sl. No. Items in competitive pressure Factor


1. Deregulation of interest rates created a healthy competitions 0.9234 0.7449

2. Capital adequacy norms has given freedom to manager of finance 0.7908

3. Competition in providing value added services to customers 0.7246

The higher factor leadings of the items is identified in the case of

deregulation of interest rates created healthy competitions and capital

adequacy norms has given freedom to manages of finance since its factor

loadings are 0.9234 and 0.7908 respectively.

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Factor loading of the items in investments:-

The investments pattern may be changed due to reformation. In order

to measure such impacts, the items related to investments have been included

in the impact analysis. The official is asked to rate the above said item at five

point scale. The score of these items are included for factor analysis. The

factor analysis identifies that only two items are narrated into the investment

factor with the reliability coefficient of 0.8144. It infers that the two items in

the investment variable explains the investment factor to the extent of 81.44

percent. The factor loading of two items in the investment is shown in

Table 8.20.

TABLE 8.20

Factor loading of the items in investments

Sl. No. Items in investments Factor loading


1. Positive impact on investments by banks after reforms 0.8643 0.8144

2. Freedom of investments lead to better performance 0.7028

The positive impact on investments by banks and freedom of

investments lead to better performance are clustered into investment factor

since the above said two items have more factor loading. The factor loading

of above said two items in the investment factor are 0.8643 and 0.7028

respectively.

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Evaluation of officials view on reformation:-

The officials view on various impacts of reforms on the banking sector

has been measured with the help of the score on each important impact

identified by the factor analysis. This score on each impact are derived from

the mean score of various items included in each impact. In the present study,

the official view on nine important impacts has been measured in PUSBs,

OPRSBs and NGPRSBs separately. The difference among the officials

belonging to the three groups of banks has been analyzed with the help of one

way analysis of variants. The official’s response on the important impacts of

reformation in PUSBs, OPRSBs and NGPRSBs is exhibited in Table 8.21.

TABLE 8.21

Evaluation of officials view on important impact of reformation

Sl. No. Important impacts

Mean score among respondents in F-

Statistics PUSBs OPRSBs NGPRSBs

1. Profitability 2.3568 3.3186 3.9863 4.8188* 2. Recovery of debts 2.7145 3.5081 4.3662 3.1506*

3. General banking activities 2.5086 3.3182 3.9094 3.6369*

4. Service quality 2.4687 3.5087 3.9718 3.9024* 5. Portfolio quality 2.5144 3.6914 3.7236 3.0396* 6. Operative efficiency 2.8842 4.1213 3.8314 3.2408* 7. Liquidity 2.5067 3.6604 3.5047 3.0146*

8. Competitive pressure 3.9873 3.9082 3.7408 0.5997

9. Investments 2.5079 3.3217 3.6687 3.2069* * Significant at five percent level

313

The highly perceived impacts among the officials in PUSBs are

competitive pressures, operative efficiency and recovery of debts since the

respective mean scores are 3.9873, 2.8842 and 2.7145 respectively. Among

the officials in OPRSBs, these impacts are operative efficiency, competitive

pressure and portfolio quality since its mean scores are 4.1213, 3.9082 and

3.6914 respectively. Among the officials in NGPRSBs, these impacts are

Recovery of debts, profitability and service quality since the respective mean

scores are 4.3662, 3.9863 and 3.9718. Regarding the perception on impact,

the significant difference among the officials in three group of banks have

been identified in the case of profitability, recovery, activity, service quality,

portfolio quality, operative efficiency, liquidity and investments since the

respective F-Statistics are significant at five percent level. In total, the

officials in NGPRSBs are rating the impact of reformation at a higher rate

than others.

Association between the profile of officials and their view on important

impacts:-

The profile of the officials may be associated with their perception on

the impact of reformation on the banking sector in India. Hence the present

study has made an attempt to analyze such association with the help of one

way analysis of variance. The included profile variables are sex, age, level of

education, years of experience, number of branches worked, number of

314

departments worked, designation, monthly income, number of training

attended and banking orientation among officials. The association between

the profile of officials and their view on impacts namely profitability,

recovery of debts and general activity have been measured. The results are


TABLE 8.22

Association between the profile of officials and their view on important impacts

Sl. No.

Profile Variables F-Statistics regarding view on

Profitability Recovery of debts

General activity

1. Sex 3.0231 2.9676 3.9146* 2. Age 2.6802* 2.7644* 2.1124 3. Level of education 2.9086* 2.8188* 2.6069* 4. Year of experience 2.5144* 2.6033* 2.9197*

5. Number of branches worked 2.5088* 2.9088* 2.0214*

6. Number of department worked 2.8182* 2.7374* 2.6063*

7. Destination 2.6063 2.9194 2.5332 8. Monthly income 2.5661* 2.7336* 2.6064*

9. Number of training attended 2.0234 2.1144 2.5086*

10. Banking orientation 2.6084* 2.4908* 2.6142* * Significant at five percent level.

Regarding the perception on profitability impact, the significantly

associating profile variables are age, level of education, years of experience,

number of branches worked, number of departments worked, monthly income

315

and banking orientation since the respective ‘F’-Statistics are significant at

five percent level. The significantly associating profile variable with the

‘Recovery of debts’ impact are age, level of education, years of experience,

number of branches worked, number of departments worked, monthly income

and banking orientation since the respective ‘F’-Statistics are significant at

five percent level. Regarding the perception on activity impact, the

significantly associating profile variables are sex, level of education, years of

experience, number of departments worked, number of branches worked

monthly income, number of training attended and banking orientation since

the respective ‘F’-Statistics are significant at five percent level.

The association between the profile variables of the officials and their

view on impacts namely service quality, portfolio quality and operative

efficiency can be examined with the help of one way analysis of variance. The

resulted ‘F’-Statistics presented in Table 8.23.

316

TABLE 8.23

Association between profile of officials and their view on impacts

Sl. No. Profile Variables

F-Statistics regarding view on Service quality

Portfolio quality

Operative efficiency

1. Sex 3.1144 2.6982 2.5091 2. Age 2.6908* 2.5196* 2.4084* 3. Level of education 2.0144 2.6089* 2.5914* 4. Year of experience 2.5083* 2.8133* 2.9034*

5. Number of branches worked 2.7667* 2.1144 2.5609*

6. Number of department worked 2.4408* 2.6997* 2.8183*

7. Destination 2.9192 2.0344 3.1344* 8. Monthly income 2.5083* 2.6089* 2.7236*

9. Number of training attended 2.4608* 2.8184* 2.5237*

10. Banking orientation 2.5143* 2.0661 2.1144 * Significant at five percent level

The significantly associating profile variable with the service quality

impact are age, years of experience, number of banks worked, number of

departments worked, monthly income, number of training attended and

banking orientations since the respective ‘F’-Statistics are significant at five

percent level. Regarding the perception on portfolio quality, the significantly

associating profile variables are age, level of education, years of experience,

number of departments worked, monthly income and number training

programmes attended so far. Regarding the perception on the operative

efficiency impact, the significantly associating variables are age, level of

317

education, years of experience; number of banks worked, number of

department worked, destination, monthly income and number of training

attended so for. The difference among the officials regarding their perception

on various impacts namely liquidity, competitive pressure and investments

were measured with the help of one way analysis of variance. The result of

the one way ANOVA is given in Table 8.24.

TABLE 8.24

Association between profile of Officials and their view of impacts

Sl. No. Profile Variables

‘F’-Statistics regarding view on

Liquidity Competitive Pressure Investments

1. Sex 3.0142 2.6081 3.3643 2. Age 2.5687* 2.7339* 2.0774 3. Level of education 2.5028* 2.114 2.1086 4. Year of experience 2.4819* 2.6087* 2.3987*

5. Number of branches worked 2.6087 2.1108 1.8984

6. Number of department worked 1.4409 2.0912 2.3904*

7. Destination 3.1466* 3.2403* 3.0664* 8. Monthly income 2.5081* 2.8187* 2.9306*

9. Number of training attended 2.6626* 1.9366 2.0144

10. Banking orientation 2.4488* 1.8024 1.5069 * Significant at five percent level

The significantly associating profile variables with in the perception on

liquidity impact are age, level of education, year of experience, designation,

monthly income, number of training attended and banking orientation since

318

the respective ‘F’-Statistics are significant at five percent level. Regarding the

officials view on competitive pressures, significantly associating profile

variables are age, years of experience, designation and monthly income

whereas regarding perception on investments, this profile variables are years

of experience, number of departments worked, designation and monthly

income since the respective ‘F’-Statistics are significant at five percent level.

Discriminant response by the officials in PUSBs and OPRSBs: -

The perception on reformation on the banking sector among the

officials in public and old private sector may differ since they are belonging

to different set of organizational structure. The perception on various impacts

variables may differ among different group of officials. It is imperative to

identify the important discriminant impact variables among the group of

officials with the help of two group discriminant analysis. Initially, the mean

difference on the perception on various important impacts and its statistical

significant has been computed. The discriminant power of the important

impacts has been examined with the help of Wilk’s Lambda. The results are


319

TABLE 8.25

Mean difference and discriminant power of important impacts in public and old private sector banks

Sl. No

Important impacts

Mean score in Mean difference

T-Statistics

Wilk’s Lambda OPRSBs PUSBs

1. Profitability (x1) 3.3186 2.3568 0.9618 2.9503* 0.2163

2. Recovery of debts (x2)

3.5081 2.7145 0.7936 2.7884* 0.1891

3. General banking activities (x3)

3.3182 2.5086 0.8096 2.8187* 0.2939

4. Service quality (x4)

3.5087 2.4687 1.0400 2.5692* 0.3108

5. Portfolio quality (x5)

3.6914 2.5144 1.1770 2.9094* 0.1455

6. Operative efficiency (x6)

4.1213 2.8842 1.2371 3.1408* 0.1319

7. Liquidity (x7) 3.6604 2.5067 1.1537 3.0687* 0.1801

8. Competitive pressure (x8)

3.9082 3.9873 -0.0791 -0.1433 0.5869

9. Investments (x9) 3.3217 2.5079 0.8138 2.5184* 0.4142 * Significant at five percent level

The higher mean difference in perception by the officials in old private

sector banks and public sector banks is identified in the case of operating

efficiency; portfolio quality and liquidity since the respective mean difference

are 1.2371, 1.1770 and 1.1537. The significant mean difference is noticed in

all nine impacts identified by factor analysis except on the competitive

pressure since the respective 't'-Statistics significant at five percent level. The

higher discriminant power is identified in the case of operative efficiency,

portfolio quality and liquidity since the respective Wilk’s Lambda coefficients

are 0.1319, 0.1455 and 0.1801.

320

The significant impacts have been included to establish two groups

discriminant function. The below mentioned procedure have been followed to

establish such function. The established function is

Z=1.3345+0.3114 X1 + 0.2917 X2 + 0.2863 X3 + 0.2736 X4 + 0.1019 X5 +

0.3143 X6 + 0.0969 X7 + 0.1033 X8

The relative contribution of each discriminant impact in the total

discriminant score is computed by the product of discriminant coefficient and

the respective mean difference of important impacts. The relative contribution

of discriminant impact in total discriminant score is shown in Table 8.26.

TABLE 8.26

Relative importance of each discriminant impacts in total discriminant score (TDS)

Sl. No.

Important impacts

Canonical Discriminant Coefficient

Mean difference Product

Relative contribution in

TDS 1. Profitability 0.3114 0.9618 0.2995 17.11 2. Recovery 0.2917 0.7936 0.2315 13.22 3. Activity 0.2863 0.8096 0.2318 13.24

4. Service quality 0.2736 1.0400 0.2845 16.25

5. Portfolio quality 0.1019 1.1770 0.1199 6.85

6. Operating efficiency 0.3143 1.2371 0.3888 22.21

7. Liquidity 0.0969 1.1537 0.1118 6.38 8. Investment 0.1033 0.8138 0.0830 4.74

Total 1.7508 100 Percent of cases correctly classified: 73.64

321

The higher discriminant coefficient is identified in the case of

operating efficiency, profitability, and recovery since the respective canonical

discriminant coefficient is 0.3143, 0.3114 and 0.2917. It infers that the degree

of influence of the above said impacts in the discriminant function is higher.

The higher relative contribution in total discriminant score is identified in the

case of operating efficiency, profitability and service quality since the

respective relative contribution in TDS is 22.21, 17.11 and 16.25. The percent

of cases correctly classified by the established dicriminant function is to the

extent of 73.64 percent. It reveals that the important discriminant impact

among the officials in old private and public sector banks are operating

efficiency, profitability and service quality.

Discriminant response by the officials in New private sector banks and

public sector banks:-

The perception on important impacts of reforms on the banking sector

in India among the officials in NGPRSBs and PUSBs may be differing from

each other. Because the organizational setup and the target for achievement

among these two group of officials are different. In order to identify the

important discriminant impact variables among this two group of officials,

initially, the mean difference in each important impact and its statistical

significance has been computed. The discriminant power of the impacts is

examined with the help of Wilk’s Lambda as illustrated in Table 8.27.

322

TABLE 8.27

Mean difference and discriminant power of important impact in new generation private sector banks and public sector banks

Sl. No.

Important Impact


T-Statistics

Wilk’s Lambda NGPRSBs PUSBs

1. Profitability (x1) 3.9863 2.3568 1.6295 3.8914* 0.1017 2. Recovery (x2) 4.3662 2.7145 1.6517 3.9309* 0.1223 3. Activity(x3) 3.9094 2.5086 1.4008 3.3943* 0.2147

4. Service quality(x4)

3.9718 2.4687 1.5031 3.6069* 0.1868

5. Portfolio quality(x5)

3.7236 2.5144 1.2092 3.1166* 0.3991

6. Operating efficiency (x6)

3.8314 2.8842 0.9472 2.9346* 0.2644

7. Liquidity(x7) 3.5047 2.5067 0.9980 2.9943* 0.2107

8. Competitive pressure(x8)

3.7408 3.9873 -0.2465 -0.5166 0.5849

9. Investment(x9) 3.6687 2.5079 1.1608 3.0144* 0.6117 * Significant at five percent level

The table–27 explains the mean of perception on nine important

impacts, its mean differences and its statistical significance. The significant

mean difference is identified in all important impacts except competitive

pressure since the respective 't'-Statistics are significant at five percent level.

The higher mean difference is noticed in the case of recovery, profitability

and service quality since the respective mean differences are 1.6517, 1.6295

and 1.5031. It infers that the officials in NGPRSBs perceive more on impacts

regarding all nine impacts of reformation especially recovery, profitability

and service quality. The higher discriminant power of the impact is noticed in

the case of profitability recovery and service quality since the respective

323

Wilk’s Lambda is 0.1017, 0.1223 and 0.1868. It reveals that the above said

three impacts discriminates the two groups of officials to a greater extent

regarding their perception on various impacts of reformation. The significant

impacts are included for the establishment of two discriminant function. The

un-standardized procedure has been followed to establish the discriminant

function.

The established function is:

Z=1.8189 + 0.2896 X1 +0.1011 X2 +0.1719 X3 +0.2139 X4 +0.0708 X5 +

0.3344 X6 +0.1729 X7 + 0.0407 X9

The relative contribution of discriminant impact in total discriminant

score is estimated by the product of the discriminant coefficient and mean

difference of the important impacts. The results are shown in Table 8.28.

324

TABLE 8.28

Relative contribution of discriminant impact in total discriminant score (TDS).

Sl. No.

Important impacts



Relative contribution

in TDS

1. Profitability 0.2896 1.6295

0.4719 25.88

2. Recovery 0.1011 1.6517 0.1669 9.15 3. Activity 0.1719 1.4008 0.2408 13.21

4. Service quality 0.2139 1.5031 0.3215 17.63

5. Portfolio quality 0.0708 1.2092 0.0856 4.69

6. Operating efficiency 0.3344 0.9472 0.3167 17.37

7. Liquidity 0.1729 0.9980 0.1726 9.49 8. Investment 0.0407 1.1608 0.0472 2.58

Total 1.8232 100 Percent of cases correctly classified: 69.73

The higher discriminant coefficient is identified in the case of

operative efficiency and profitability since the respective discriminant

coefficients are 0.3344 and 0.2896 respectively. It infers that the degree of

influence of these two impact namely operative efficiency and profitability on

discriminant function is relatively higher. The higher relative contribution in

total discriminant score is identified in the case of profitability, service quality

and operative efficiency since the respective relative contributions are 25.88,

17.63, 17.37 percent respectively. The percent of cases correctly classified by

the established discriminant function is 69.73 percent. The analysis reveals

325

that the important discriminant impact among the officials in NGPRSBs and

PUSBs are profitability, service quality and operative efficiency.

Discriminant response by the officials in NGPRSBs and OPRSBs:-

The perception on reformation among the officials in NGPRSBs and

OPRSBs may differ because of their organizational structure and setup. It is

highly imperative to analyze the impact on which the two groups of officials

are significantly differing from each other and also the discriminant impacts

among the two groups. Initially, the mean difference in each impact, its

statistical significance and the discriminant power of the impact has been

measured. The results are presented in Table 8.29.

TABLE 8.29

Mean difference and discriminant power of important impact in NGPRSBs and OPRSBs.

Sl. No

Important impacts


T-Statistics

Wilk’s Lambda NGPRSBs OPRSBs

1. Profitability (x1) 3.9863 3.3186 0.6677 2.5193* 0.1893

2. Recovery of debts (x2)

4.3662 3.5081 0.8581 2.9096* 0.1214

3. General banking

activities (x3) 3.9094 3.3182 0.5912 2.2087* 0.2313

4. Service quality (x4)

3.9718 3.5087 0.4631 1.8183* 0.1963

5. Portfolio quality (x5)

3.7236 3.6914 0.0322 0.2244 0.3161

6. Operative efficiency (x6)

3.8314 4.1213 -0.2899 -1.4433 0.5969

7. Liquidity (x7) 3.5047 3.6604 -0.1557 -1.0021 0.4474

8. Competitive pressure (x8)

3.7408 3.9082 -0.1674 -1.0682 0.5768

9. Investments (x9) 3.6687 3.3217 0.3470 1.6508* 0.4562 * Significant at five percent level.

326

The significant mean difference among this two the group of officials

is noticed in the case of profitability, recovery, activity, service quality and

investments since the respective 't'-Statistics are significant at five percent

level. The higher mean difference is identified in the case of recovery of

debts, profitability and activity. The higher discriminant power is identified in

the case of recovery of debts; profitability and service quality since the

respective Wilk’s Lambda are 0.1214,.1893 and 0.1963. The significant

impacts are included to establish the two group discriminant function. The

below stated procedure is followed to established the function. The

established function is:

Z= 0.8177+0.1919 X1+0.2483 X2+0.2908 X3 +0.3391 X4+0.1082 X9

The relative contribution of each impact in total discriminant score is

estimated by the product of discriminant coefficient and the respective mean

difference of the impact. The resulted discriminant coefficient and the

respective relative contribution in total discriminant score is shown in

Table 8.30.

327

TABLE 8.30

Relative contribution of important impact in Total discriminant score (TDS)

Sl. No.

Important impacts



Relative contribution

in TDS 1. Profitability 0.1919 0.6677 0.1281 18.10 2. Recovery 0.2483 0.8581 0.2131 30.12 3. Activity 0.2908 0.5912 0.1719 24.29

4. Service quality 0.3391 0.4631 0.1570 22.19

5. Investment 0.1082 0.3470 0.0375 4.70

Total 0.7076 100

Percent of cases correctly classified: 68.14

The higher discriminant coefficient is noticed in the case of service

quality, activity and recovery of debts respectively. It infers that the above

said important impacts have influence in the discriminant function compared

to other impacts. The higher relative contribution in total discriminant score is

identified in case of recovery, activity and service quality since their

respective contributions are 30.12, 24.29 and 22.19 percent to the total. The

percent of cases correctly classified by the established discriminant function is

68.14 percent. The analysis reveals that the important discriminant impact

among the officials belonging to NGPRSBs and OPRSBs are recovery of

debts, general banking activity and service quality.

328

Overall attitude of officials towards the impact of reformation in banking

sector:-

The overall attitude towards the impact of reformation in banking

sector is measured at five point scale namely highly satisfied, satisfied,

moderate, dissatisfied and highly dissatisfied. The distribution of officials on

the basis of their overall attitude is given in Table 8.31.

TABLE 8.31

Overall response of bank officials towards the reformation in banking sector

Sl. No. Overall attitude

Number of respondents in Total PUSBs OPRSBs NGPRSBs

1. Highly satisfied 17 27 25 69 2. Satisfied 27 36 37 100 3. Moderate 41 39 38 118 4. Dissatisfied 29 20 22 71 5. Highly dissatisfied 26 18 18 62

Total 140 140 140 420

The important overall attitude towards reformation in banking sector

among the officials is moderate and satisfied which constitute 28.09 and

23.81 percent to the total respectively. In total, 14.76 percent of officials are

highly dissatisfied towards the reformation. The most important overall

response of the bank officials towards reformation in PUSBs is moderate

which constitutes 29.29 percent to its total. In the case of OPRSBs and

NGPRSBs, this is also moderate which constitutes 27.86 and 27.14 percent to

its respective total.

329

Effect of response on individual impacts on the overall attitude towards

reformation among PUSBs officials:-

The perception on various impacts of reformation may have its own

influence on the overall attitude towards reformation. It is highly essential to

analyze the highly influencing perception of impact on the overall attitude for

some policy implication. The impacts analysis is carried out with the help

multiple regression analysis. The fitted regression model is

Y=a+b1x1+b2x2+b3x3+b4x4+b5x5+b6x6+b7x7+b8x8+b9x9+e

Whereas

Y = Score on overall attitude towards reformation (Highly satisfied-5;

satisfied-4; Moderate-3; dissatisfied-2 and highly dissatisfied-1)

X1 = Score on the perception on profitability

X2 = Score on the perception on Recovery

X3 = Score on the perception on activity

X4 = Score on the perception on service quality

X5 = Score on the perception on portfolio quality

X6 = Score on the perception on operative efficiency

X7 = Score on the perception on liquidity

X8 = Score on the perception on competitive pressures

X9 = Score on the perception on investments.

b1, b2 ------ b9 = Regression coefficient of independent variables

a= Intercept and b=error term.

330

The regression coefficients of independent variables on the overall

attitude towards reformation is presented in Table 8.32.

TABLE 8.32

Effect of response on individual impacts on the overall attitude towards reformation among PUSBs officials

Sl. No.

Independent variables

Regression coefficients

Standard error

't'-Statistics

P-value

1. Profitability 0.1378 0.0344 4.0058* 0.0246 2. Recovery 0.2614 0.0761 3.4349* 0.0387 3. Activity 0.2407 0.05141 4.6819* 0.0194 4. Service quality 0.2891 0.0497 5.8169* 0.0133 5. Portfolio quality -0.0942 0.0861 -1.0941 0.5871

6. Operative efficiency 0.1718 0.0503 3.4155* 0.0476

7. Liquidity 0.1033 0.0962 1.0738 0.5565


9. Investments -0.0344 0.1097 -0.3135 0.7802 Constant 0.8586 R2 0.7374 ‘F’-Statistics 9.0876*

* Significant at five percent level

The significantly influencing impact on the overall attitude towards

reformation among the officials in PUSBs is profitability, recovery, activity,

service quality and operative efficiency. A unity increase in the perception on

the above said impacts result in an increase in overall attitude towards

reformation by 0.1378, 0.2614, 0.2407, 0.2891 and 0.1718 units respectively.

The changes in the perception on various impacts explain the changes in the

331

overall attitude towards reformation to the extent of 73.74 percent. The

significant ‘F’-Statistics reveals the validity of fitted regression model.


reformation among OPRSBs officials:-

The effect of perception on various individual impacts of reformation

on the overall attitude towards reformation among the officials in OPRSBs

has been analyzed separately with the help of regression analysis. The

resulted regression coefficients are summarized in Table 8.33.

TABLE 8.33

Effect of response on individual impacts on the overall attitude towards reformation among OPRSBs officials

Sl. No.



Standard error

't'-Statistics

P-value

1. Profitability 0.3144 0.1011 3.1098* 0.0363 2. Recovery 0.1637 0.1323 1.2373 0.0971 3. Activity 0.2087 0.0576 3.6232* 0.0296 4. Service quality 0.2964 0.0817 3.6279* 0.0296 5. Portfolio quality -0.0861 0.1394 0.6176 0.3144

6. Operative efficiency 0.1944 0.0708 2.7458* 0.0418

7. Liquidity -0.0687 0.1142 -0.6016 0.3396


9. Investments 0.1011 0.1486 0.6803 0.2809 Constant 1.3084 R2 0.8186 ‘F’-Statistics 13.2564*

* Significant at five percent level.

332

The significantly influencing individual impact on the overall attitude

towards reformation among the officials in OPRSBs are profitability, activity,

service quality and operative efficiency since the respective regression

coefficients are significant at five percent level. A unit increase in the

perception on the above said impacts result in an increase in the overall

attitude towards reformation by 0.3144, 0.2087, 0.2964 and 0.1944 units

respectively. The changes in the perception on the included impacts explain

the changes in overall attitude towards reformation to the extent of 81.86

percent. It infers that the important impact variables influencing the overall

attitude towards reformation are profitability, activity, service quality and

operative efficiency.


reformation among NGPRSBs officials:-

Among the officials in NGPRSBs, the impact of perception on

important impacts of reformation on the overall attitude towards the

reformation has been analyzed separately. The score on overall attitude is

treated as dependent variable whereas the score on perception on important

impacts are treated as independent variables. The multiple regression analysis

has been applied to analyze such impacts. The results are shown in

Table 8.34.

333

TABLE 8.34

Effect of response on individual impacts on the overall attitude towards reformation among NGPRSBs officials:-

Sl. No.



Standard error

't'-Statistics

P-value

1. Profitability 0.2944 0.0817 3.6034 0.0247 2. Recovery 0.1133 0.1309 0.8655 0.0816 3. Activity 0.2033 0.0466 4.3626 0.0038 4. Service quality 0.2768 0.0819 3.3797 0.0217 5. Portfolio quality -0.0917 -0.1204 -0.7616 0.1344

6. Operative efficiency 0.1408 0.1689 0.8336 0.0939

7. Liquidity 0.0525 0.0914 0.5744 0.1573


9. Investments -0.0493 0.1016 0.4852 0.3392 Constant 1.8364 R2 0.7917 ‘F’-Statistics 11.3697*


The significant regression coefficients are seen in the case of

profitability, activity, service quality and competitive pressures. It infers that a

unit increase in the perception on above said impact result in an increase in

the overall attitude towards reformation by 0.2944, 0.2033, 0.2768 and 0.1093

units respectively. The changes in the perception on various impacts included

in the analysis explain the changes in the overall attitude towards the

reformation to the extent of 79.17 percent. The analysis reveals that the

significantly influencing overall attitude towards the reformation is impact on

profitability, activity, service quality and competitive pressures.

334

Analysis for pooled data:-

In order to analyze the impact of perception on the various impacts on

the overall attitude towards reformation among the officials in all three group

of banks altogether, a separate multiple regression model is fitted. The

included independent variables are perception on profitability, recovery,

activity, service quality, portfolio quality, operative efficiency, liquidity,

competitive pressures and investments whereas the included dependent

variable is overall attitude towards the reformation. The result of regression

analysis is presented in Table 8.35.

TABLE 8.35

Impact analysis among all bank officials (Pooled data)

Sl. No.



Standard error

't'-Statistics

P-value

1. Profitability 0.2345 0.0788 2.9759 0.0447 2. Recovery 0.1902 0.0567 3.3545 0.0394 3. Activity 0.2017 0.0609 303119 0.0297 4. Service quality 0.2803 0.0711 3.9423 0.0134 5. Portfolio quality -0.0734 0.1244 -0.5900 0.2967

6. Operative efficiency 0.1517 0.0432 3.5116 0.0236

7. Liquidity 0.0669 0.1239 0.5399 0.3066


9. Investments 0.0934 0.1441 0.6482 0.3117 Constant 1.2638 R2 0.8947 ‘F’-Statistics 15.3093*


335

The significantly influencing response on individual impacts towards

the overall attitude on reformation are profitability, recovery, service quality,

operative efficiency and competitive pressures since the respective regression

coefficients are significant at five percent level. A unit increase in the

perception on above said variables result in an increase in the overall attitude

towards reformation by 0.2345, 0.1902, 0.2017, 0.2803, 0.1517 and 0.1174

units respectively. The change in the perception on the included nine impacts

explained the changes in the overall attitude towards reformation to the extent

of 89.47 percent. The analysis infers that important impacts having a

significant influence on the overall attitude towards the reformation is

profitability, recovery, activity, service quality, operative efficiency and

competitive pressures

The overall result of this analysis clearly states that the officers of all

the three group of banks were in the opinion that considerable improvement is

achieved in the areas of profitability, recovery of debt, service quality,

operative efficiency and competitive pressures of banks in Kerala after the

various reforms were implemented

response of bank officials on the impact of...

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