research journal of commerce & behavioural science - rjcbs

Volume:01, Number:03, Jan-2012 : RJCBS Page 1 www.theinternationaljournal.org

Table of Contents

Articles E-S-QUAL: MEASURING QUALITY OF E-TAILING SERVICES IN RURAL MARKET

Kannan Paul, SARAVANAN R

EI at Work Place

MONICA M, Dr. Vijayashree LAKSHMAN

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Soumik Gangopadhyay

INVESTOR ATTITUDE ON RISK AND INVESTMENT GOALS AMONG EXPATRIATE - INDIANS IN OMAN

MOHAMMED RAFIQ

Technical Analysis of Selected Indian Banks

N R Benjamin Franklin

PRE AND POST ACQUISITION PERFORMANCE OF PUBLIC AND PRIVATE SECTOR BANKS IN INDIA

shanmugam venkatesan, krishnan reddiyar Govindarajan

Book Review Book Review 99 Thoughts on Ganesha

Mrs Deepali Nilesh Pulekar


E-S-QUAL: MEASURING QUALITY OF E-TAILING SERVICES

IN RURAL MARKET

Dr. R.Saravanan,

Director, School of Management,

V.L.B.Janakiammal College of Engineering & Technology,

Kovaipudur, Coimbatore- 641 042,

P.Kannan, Asst.,

Prof., & HOD, Department of Management Studies,

N.P.R. College of Engineering & Technology,

Natham and Research Scholar,

Anna University of Technology Coimbatore,

Coimbatore.

Abstract

The present study focuses the behavior and activities of the rural people in using e-tailing. In

the research work (Parasuraman et al., 2005), E-S-QUAL 11 dimension measuring tools was

used to measure the perception and expectation of the rural people in Dharmapuri district at

the sample size of 310. This study also analyses the preference and behavior of the rural

people in their internet usage. The result of this study suggests that the E-tailing services

providers will have to improve their services in the area of design and order confirmation and

also field and age of the customer determine their behavior of spending time and choice of

websites in their internet usage.

Key words: E-S-QUAL, Perception, Expectation, Rural, Preference


1. Introduction:

E-tailing is the largest marketing activity in the rapidly growing field of electronic commerce

and, logically, perceived service quality would seem to be the key success factor that lifts this

new form of retailing above traditional retailing because the products the two types of

retailers sell are the same. However, e-retailing service quality must be validly measured if its

actual role is to be demonstrated empirically. Moreover, a valid measure of service quality at

each stage of e-retailing is required if e-retailers seek to improve their service quality.

1.1 E-tailing:

E-tailing is ―retailing conducted online, over the internet‖ (Turban et al. 2006, p. 83); it is

also called B2C e- commerce which refers to retail transactions of products or services from

businesses to individual customers. In this study e-tailing and B2C e-commerce are viewed as

equivalent, and these two terms are used interchangeably. Even though the most common use

of e-tailing is the sale of products or services online, but online retailing businesses do not

only undertake simple sales, they also include other applications, as do physical retailing

outlets. Some of those applications include:

1. Selling goods and testing new products: Many giant retailers use the internet as a tool to

test new products and services. This strategy is useful to reduce risks in the early stages of

new product marketing and sales (Mullaney 2004).

2. Market research: Retailers can use their online presence to gain valuable customer

information for predication of future customer demand. In the offline environment, such data

are difficult and expensive to collect and analyse (Rao 1999). Online market research has

some powerful advantages, such as monitoring real-time buying decision with more accurate

and reliable data (Baker 2005).

3. Promotional tool: Following on from market research, valuable customer data can be

used to conduct pricing and promotional experiments. A website can be used as a tool to

conduct promotional experiments, due to the wide reach of the internet and its cost-

effectiveness (Rao 1999).

4. Marketing tool: A website can also be an effective channel to communicate with

customers (Peterson et al. 1997). The internet has made businesses dream of interactivity,

personalization, customization and 24/7 availability a reality.

5. Online customer service: Many new services (i.e., delivery status information and

personalised products) can be available uninterrupted online, which is almost impossible or

too expensive to have in the physical world.

2. E-TAILING SUCCESS FACTORS

E-commerce system can be measured in four dimensions: system quality, content quality,

trust and support & services (Molla & Licker 2001). Findings from researchers such as

Chiger (1997), Nielsen (1998) and Lohse and Spiller (1998) point out that poor e-commerce

system quality of websites will have a negative influence on the customers‘ online shopping

experience and their satisfaction with the sites. Due to the nature of the virtual environment,

customers cannot physically touch the products before purchasing from websites. The

website is the only channel to understand a product. As a result the content on the site should

be functional and attractive. Some researchers (i.e., Von Dran et al. 1999; Zhang et al. 2000)

argue that content quality may be more important than system quality. In content quality as

well as in system quality, research findings have suggested that trust (including attributes of

security, privacy, and product quality) has an important effect on the use of e-commerce and

user satisfaction, due to the high uncertainty of the online environment (Gefen et al. 2003;

Urban et al. 2000). Another important factor of website quality is support & services


(including FAQs section on the website, online customer services facilities, search function

within the site, online feedback & review facilities, online payment and delivery services,

online customization tools, escrow & insurance services, etc) provided by a website. Service

quality is increasingly recognised as an important aspect of e-commerce (Santos 2003). Past

studies (i.e., Aberg & Shahmehri 2000; Chen et al. 2004; Genfen & Devin 2001; Madeja &

Schoder 2003; Page & Lepkowska-White 2002; Parasuraman et al. 1988; Santos 2003) have

suggested that service quality is positively related to the success of e-commerce. In the

meantime, many previous research (e.g. Barnes et al. 2004; Gibbs 2002; Leonard et al. 2003;

Sabherwal et al. 2004; Gibbs et al. 2002; Molla 2004) also has investigated the factors

affecting the adoption of e-commerce from different perspectives, including senior

management factor, organisational factor, e-commerce strategy, consumer factor, and

external factor.

According to the discussion above, a theoretical framework (see Figure-1) was developed

from the literature review, and served as theoretical foundation of the following empirical

case study research. Six factors are included in the framework, namely, (1) organizational

factor; (2) senior management factor; (3) e-commerce strategies; (4) external factor; (5)

consumer factor; and (6) e-commerce system measurement.

3. Review of Literature:

J. J. Cronin, et al., (2000) their study shows that online service quality may impact e-tail

success through online customer satisfaction and loyalty. Although the SERVQUAL is a

valuable analytical tool for IS managers, the SERVQUAL metrics needs continued

development and validation.

Tobias gunnesson and Klas sodelund (2001) study tries to go beyond how an e – retailer can

create competitive advantages with regards to existing retailers of how they can improve its

competitive positioning through e-retail. Quality management systems are needed to provide

a consistent way to select, evaluate, prioritize and plan the right e-services. The increasing

use of e-services has raised the need to define standards and means to assess and assure

quality. Investment in e-services is an important step to improve the quality of life in our

dynamic society.

Childers et al. (2001), Erogolu et al. (2003), Mummalaneni (2005) study within the e-retail

literature support the notion that flow-like experiences occurring during e-service encounters

are primarily driven by Web-based characteristics (such as the presence of multimedia, Web

atmospherics, interactivity, product-related information content) and when the consumer has

a high degree of perceived control during the process of Website navigation.

Rossiter‘s (2002) C-OAR-SE construct measurement theory is then applied to develop a new

and more valid measure, called ER-SERVCOMPSQUAL. This new measure seeks potential

customers‘ and current customers‘ judgments about the quality of the components of e-retail

service (thus ensuring high item-content validity), which are rated in terms of behavioral

answer categories (which have high answer-scale validity).

Srini S. Srinivasana et al., (2002) investigated the antecedents and consequences of customer

loyalty in an online business-to-consumer (B2C) context. They identified eight factors (the

8Cs—customization, contact interactivity, care, community, convenience, cultivation, choice,

and character) that potentially affect e-loyalty and developed scales to measure these factors.


R. E. Anderson and S. S. Srinivasan, (2003), H. E. Yang and K. H. Yeh, (2006), in their

research work pin point that the measure of perceived quality, satisfaction, and loyalty on

behalf of customers have been used to assess firm‘s productivity and its marketing

performance in the service industry.

Specifically, when the items were used to assess the IS success, the wordings and the validity

assessment of the SERVQUAL scales are required (Y. S. Wang and T. I. Tang , 2003). Based

on D&M IS Success Model, the authors of reference (W. Rodgers, S. Negash, and K. Suk,

2005) proposed a general model of online satisfaction including three dimensions of e-quality

– system quality, information quality, and service quality. System quality describes measures

of the information processing system, such as ease of access to and interaction with the

system. Information quality represents measures of information system output, such as

informativeness and entertainment of the information provided by the online service.

Vargo and Lusch‘s (2004) argued against this distinction. It is a distinction that necessitates

some differences in the measurement items. ER-SERVCOMPSQUAL has separate sections

to accommodate this distinction and, also, the questionnaire is easily adapted to fit different

categories of e-retailers within products and services.

Parasuraman et al.‘s (2005) E-S-QUAL (and E-RecS-QUAL) multiple-item scale, is shown

to be based on an inadequate conceptual definition. Their definition of the E-RETAILING

object of the construct identifies only two stages of e-retailing whereas the definition for the

new measure, ER-SERVCOMPSQUAL, identifies six stages in the overall e-retailing

process. Nor does E-S QUAL distinguish e-retailers who sell products from those who sell

services.

H. E. Yang and K. H. Yeh, (2004) studied that consumer satisfaction has been the subject of

much attention in the literature because of its potential influence on consumer behavioral

intention and customer retention.

Orit and Ilan (2005), in their study found a conceptual model of the decisions households

make with regard to information gathering, purchase transactions and delivery mode. Data on

revealed behavior and various socio-demographic and economic characteristics of shoppers

was collected in the Tel-Aviv Metropolitan area in the summer of 2004. Their study focused

on the consumers‘ purchase and delivery (PD) choices, as part of a broader effort to

understand consumers‘ shopping behavior.

The present article begins by criticizing the content validity of E-S-QUAL (Parasuraman,

Zeithaml, and Malhotra 2005), the principal academic measure of e-retailer service quality,

which is probably the most important construct in contemporary services research.

Joel E. Collier et al., (2006) in their article extended the work on e-service quality to

encompass not only Web site interactivity or process quality but also outcome quality and

recovery quality. A conceptual framework of e-service quality is proposed and empirically

tested that combines process, outcome, and recovery dimensions. Contrary to previous

service quality studies, formative instead of reflective indicators are used to conceptualize e-

service quality. Their study found empirical support for the use of formative indicators and

the three-dimensional approach to conceptualizing e-service quality.


Liao.C, et al., (2006) evaluated using structural equation modeling. Results show that

consumers‘ behavioral intentions to continue using a B2C web site are determined by all

three key drivers: perceived usefulness, trust, and habit. Furthermore, not all dimensions of

web quality have a significant effect on perceived usefulness and trust.

Hao-erl Yang,s (2007), study stated that e-quality metric needs continued development and

validation when measuring customer‘s satisfaction and loyalty in e-shopping environment.

Adding the newly developed service quality scales E-S-Qual to the D&M IS Success Model

to assess a website loyalty model.

Jamie Carlson, Aron O‘Cass (2009), study examined that impact of e-service quality

attributes on the development of flow, and further investigates the impact flow has on

consumers‘ Website loyalty and word-of-mouth behavior. Most companies try their best to

continually satisfy their customers because customer satisfaction seems to be an important

barometer of customer‘s behavioral intentions and has been regarded as an important

antecedent of loyalty.

Eduard Cristóbal Fransi and Frederic Marimon Viadiu, paper analyzed various elements that

influence the purchasing behaviour of online consumers. These elements include the aesthetic

aspects of a website and the interactive processes that take place at the time of purchase. The

study analyses the expectations and perceptions of a sample of Spanish online customers. On

the basis of these attitudes, the sample of respondents is segmented. In addition, the main

factors that determine online service satisfaction are identified. The analysis thus allows

differentiation of both customers and service quality. The paper concludes with

recommendations for online retailers who wish to operate a successful ‗virtual‘ retail outlet.

Noor et al., (2007), study explored the internet service quality in service industry

particularly in e-ticketing for transportation services. The primary data for this study was

collected through web observation. Result shows that appearance and linkages are among

the two most important determinants that should be used when measuring the quality of

internet services. Through the findings, a guideline of the transportation websites regarding

the important features could be developed. The findings show that e-ticketing websites would

be an advantage to have all these features in order to increase user satisfaction in

doing online transactions.

Nittana Sukasame focused on the e-service quality dimensions in successfully

establishing e-commerce ventures. Consequently, success is measured in terms of growth

rate. The following factors selected from previous studies on e-service quality linked

to successful e-commerce entrepreneurs are proposed: content, accessibility, ease of

use, reliability, responsiveness, and security. Additionally, the factor linked specifically

to e-service domain enhancing automatic tasks such as self-service technology is

examined. His study could generate different views on the e-service quality paradigms

associating with the competitive success of the e-commerce entrepreneurs.

Juan‘s study reviewed the quality of customer service (E-S-QUAL) model and the quality of

service recovery (E-RecS-QUAL) model and applied them to the African American and

Chinese cultural settings.


Objectives of the study:

The primary objective of the study is to measure the quality of e-tailing services among rural

people in Dharmapuri district. The secondary objectives are

To compare the rural people perception and expectation of e-tailing in Dharmapuri

district.

To analyze the demographic profile of the rural people.

To measure the behavior of the internet user in rural people.

Hypothesis Testing

Ho: There is no significance relation between age group of the respondents and On average

number of internet visits per week


Minutes of web site visit


Minutes spend with specific web site

4. Research Methodology:

Descriptive research design was used with 310 respondents. Finally, the researcher filtered

and selected 300 valid responses out of 310. The primary data and secondary data are

collected. Primary data is collected from E-S-QUAL, a 50 item scale used to collect the

primary data. The secondary data are collected from the articles, newspaper, books and

internet. Five point scales was used in measuring the perception of rural customers. The

percentage method and Weighted mean values of E-S-QUAL Score are used to measure the

quality of e-tailing. SPSS package was also used to measure the mean value and cross

tabulation of Service quality of e-tailing. The scope of the study is to know the perception

and expectation of rural people. Another one is to measure the quality of e tailing services in

among rural people.

5. Result and Discussion

Figure 5.1shows that 23.3% of the respondents are from the age group of 35 and above and

15% of the respondents come under 31 to 35 age frame. Figure 5.2 shows that 18% of the

respondents are from Medical field and 11% of the respondents from Management field.

Fig. 5.3 Different website Visiting habits of the Respondents

< 21 20%

21-25 20%

26-30 22%

31-35 15%

35 < 23%

Fig. 5.1 Age wise Calssifcation

Engineering

15%

Medical 18%

Marketing

17%

Management 11%

Social science

15%

Accounting

12%

Law & others

12%

Fig. 5.2 Field of the Respondents


19%

17%

20%

23%

21%

Book Store

20%

21%

19%

20%

20%

Movie Store

22%

20%

16%

21%

21%

Music Store

23%

24%

15%

17%

21%

Second Hand Products

18%

20%

22%

23%

17%

Search Engines

19%

19%

21%

20%

21%

E shop

Never day once a year once a month once a week once a or more


Figure 5.3 shows that 22.3% of the respondents visit book store once in a week, 23.7% of

rural people Never visit Music store in a day, 23% of the respondents never visit second hand

products sale website due to the reason that they have habit of buying second hand products

personally. 22 % of the respondents are using search engines for their multiple purposes once

a month and 20% of the respondents are have the habit of visiting e shopping website once a

week

The above figure 5.4 indicates that 23.7% of the respondents spent 31 to 40 minutes in a

week and 17% of the respondents spent below 10 minutes and 21 to 30 minutes in a week.

Figure 5.5 indicates that 21.3% of the respondents stay below 10 minutes in a website and

20% of the respondents stay for 31 to 40 minutes in a website. These habits show that people

have interest to visit website and stay in very minimum time. Since they are using internet

and visiting some website they had compulsion to go to a browsing centre. The browsing

centre‘s are normally charging Rs. 15/- to Rs.30/- Per hour.

TABLE 5.1 Correlation Values of Perception and Expectation of Rural people

Dharamapuri District

Sl.No SERVQUAL Dimension Correlation value

1 Clarity of purpose -0.99

2 Design 0.14

3 Communication -0.80

4 Assurance 0.19

5 Service and Frequently Asked Questions 0.54

6 Accessibility and speed 0.91

7 Product or service choice 0.86

8 Order confirmation -0.36

9 User recognition -0.65

10 Extra service 0.24

11 Frequent buyer incentives 1.00

The above table clearly explains the correlation of perception and expectation of rural people

in Dharmapuri District an e-tailing services. Clarity of purpose, communication, order

Confirmation, and user recognition got negative correlation. The service providers

concentrate on these dimensions. The rural people have different opinion on the e tailing

Below 10

17%

11 to 20 20%

21 to 30 17%

31 to 40 23%

41 above 23%

Fig. 5.4 Time Spend on a Website

Below

10 21%

11 to 20 21%

21 to 30 20%

31 to 40 20%

41 above 18%

Fig.5.5 Time do they Stay in a WebSite


services in the area of purpose and communication. Some of the website and e tail service

provider are using wage English. It creates some misunderstanding and confusion. At the

same time they had confusion on order confirmation. They ask too much of details to

confirm the order. The rural people don‘t like it. The service providers can reduce some

details in the order confirmation form. The same problem happens in user recognition.

Above figure 5.6 indicates that rural people from Dharamapuri District have variation in their

perception and expectation. They had some amount of mismatch between their perception

and expectation of Clarity of purpose, Communication, Order confirmation and User

recognition. The reason these dimensions got negative correlation.

Table No. 5.2 Correlation Analysis Field of the respondents and visiting different

website

S.No Particulars Spearman Correlation

R

Value

Asymp.

Std.

Errora

Approx.

Tb

Approx.

Sig

1 Correlation between respondents Field and

habits of visiting Book store Website

.050 .058 .857 .392c


habits of visiting Music store Website -.064 .056 -1.102 .271

c


habits of visiting Search engine store Website

.073 .059 1.266 .206c


habits of visiting Second hand products sale

Website

.096 .058 1.662 .098c


habits of visiting Movies store Website

.062 .057 1.074 .284c


habits of visiting E shop Website

.053 .059 .911 .363c

Table 5.2 clearly shows the relation between field of the respondents and visiting habits of

different website like Book store, Music store, search engine, second hand products, movies

store and e shop. All the category of website got positive correlation Out of music store. The

reason is that hearing and downloading music never considers the field. Everyone have

habits of hearing music and interest to download new songs.

D1 D2 D3 D4 D5 D6 D7 D8 D9 D10 D11

Dharmapuri -0.99 0.14 -0.80 0.19 0.54 0.91 0.86 -0.36 -0.65 0.24 1.00

-1.50

-1.00

-0.50

0.00

0.50

1.00

1.50

Val

ue

Fig. 5.6 Correlation Value Analysis


Table No. 5.3 Hypothesis testing

S.No Hypothesis Testing Pearson

Chi-

Square

value

Asymp.

Sig.

(2-sided)

Results

1 There is no significance relation between age

group of the respondents and On average number

of internet visits per week

13.974 .601 Rejected


group of the respondents and On average Minutes

of web site visit



group of the respondents and On average Minutes

spend with specific web site


Table 5.3 describes that there is a significance relation between age group of the respondents

and an average number of internet visits per week, an average minutes of website visit and

time spent with specific website. Because age is the main force to determine the duration to

spend with particular website and frequency of using internet. Based on the age level the

categories of website also vary.

Table 5.4 E-S-QUAL dimension Descriptive Value (Mean and Standard Deviation):

S.no Particulars Perception Expectation P-E

GAP Clarity of purpose Mean S.

D

Mean S.D

1 The purpose is clear 3.05 1.44 2.95 1.43 0.1

2 Finding your way on the web site is easy. 2.97 1.36 3.02 1.40 -

0.05*

3 Instructions are directly available 3.02 1.46 2.97 1.45 0.05

Design

4 The number and type of links are meaningful 3.02 1.45 3.02 1.44 0

5 Navigation is consistent and standardized 3.05 1.40 3.06 1.36 -

0.01*

6 A standard navigation bar, a home button and

back/forward button are available on every page

3.04 1.41 3.05 1.37 -

0.01*

7 Opening of new screen is kept to a minimum 2.94 1.48 3.06 1.46 -

0.12*

8 It is easy to print from the web 3.02 1.37 2.99 1.42 0.03

9 Information is found with a minimum of click 3.18 1.40 3.07 1.42 0.11

10 There are well programmed search options 3.04 1.44 2.89 1.42 0.15

11 Forms to enter personal details are self-

explanatory

3.02 1.43 2.99 1.36 0.03

Communication

12 Scrolling through pages and text is kept to a

minimum

2.98 1.40 3.11 1.34 -

0.13*

13 Colors, pictures and images are consistent,

relevant and clear

3.03 1.35 2.89 1.42 0.14

14 Web sites animations are meaningful 2.86 1.40 3.13 1.43 -

0.27*


Assurance

15 The security policy is accessible 2.99 1.36 2.81 1.42 0.18

16 The privacy policy is accessible 2.95 1.40 2.99 1.43 -

0.04*

17 The web sites contains company details 2.92 1.42 2.98 1.41 -

0.06*

18 External validation of trustworthiness is

important

3.24 1.43 3.00 1.43 0.24

19 Brand images is important 2.93 1.44 2.94 1.45 -

0.01*

Service and Frequently Asked Questions

20 An email address for queries and complaints is

provided

3.13 1.44 3.07 1.46 0.06

21 Queries or complaints are resolved within 24

hours

2.96 1.43 2.88 1.44 0.08

22 User feedback is sought to measure customer

satisfaction

3.11 1.37 3.06 1.39 0.05

23 Information is provided to Frequently Asked

Questions and answers

3.04 1.39 3.02 1.39 0.02

24 The Frequently Asked Questions and answers

contain links that take the user to the relevant

page

3.10 1.46 2.86 1.41 0.24

Accessibility and speed

25 24*7*365 user accessibility 3.02 1.44 3.03 1.46 -

0.01*

26 Page availability information is given on entry 3.23 1.43 3.15 1.38 0.08

27 Access is fast 2.96 1.42 2.94 1.47 0.02

28 Graphics and animations do not detract from use 2.95 1.47 2.84 1.44 0.11

Product or service choice

29 Full product or service characteristics are

available

3.18 1.45 3.04 1.41 0.14

30 Full detail of product or service pricing are

available

2.98 1.42 3.04 1.44 -

0.06*

31 Required stock information is available

throughout the buyingprocess

2.84 1.37 2.97 1.39 -

0.13*

Order confirmation

32 Tax and/or other charges are clearly detailed 3.00 1.38 2.99 1.38 0.01

33 Terms and conditions of sales are accessible 3.05 1.42 3.04 1.42 0.01

34 Access to anticipated delivery times is available

at all times Product purchase

2.92 1.39 3.08 1.36 -

0.16*

35 The user can make a purchase without web site

registration

3.06 1.43 2.94 1.38 0.12

36 Different payment options are stated clearly 3.02 1.38 2.95 1.42 0.07

36 A complete overview of the order is presented

before final purchase decision

3.00 1.41 3.04 1.53 -

0.04*

38 All relevant order confirmation details are sent by

email within 24 hours

3.01 1.45 2.95 1.34 0.06

39 Order tracking details are available until delivery 3.00 1.40 3.04 1.43 -


0.04*

40 Order cancellation and return details are confirm

within three days

2.83 1.40 3.01 1.41 -

0.18*

User recognition

41 The registration process is simple 3.00 1.43 3.05 1.40 -

0.05*

42 Registration process details are retained 3.03 1.45 3.15 1.44 -

0.12*

43 The home page features options for new and

registered users

3.07 1.47 2.90 1.43 0.17

Extra service

44 A customer platform is provided for exchange of

ideas

2.94 1.44 2.84 1.41 0.1

45 Links are provided to pages on related products

and services

3.04 1.38 3.01 1.47 0.03

46 Search on related sites are provided (e.g. a

hotel/flight search on travel sites)

3.02 1.38 2.99 1.40 0.03

47 The user can customized the web sites and the

information is retained

2.82 1.37 3.01 1.45 -

0.19*

48 Web sites that focus on brand awareness have a

store locator

3.01 1.40 3.14 1.40 -

0.13*

Frequent buyer incentives

49 The user is invited into a frequent buyer program 2.93 1.41 3.25 1.38 -

0.32*

50 The web site offers free shipping and handling

within a set of rules

2.86 1.39 3.08 1.45 -

0.22*

N-300 Min-1 Max-5

*Negative Gap Score

The above table shows the mean variances between rural people perception and exception.

Assurance, design, Product or service choice and order confirmation got more negative score.

The e tailing service providers should concentrate on these dimensions to provide better

service in future.

6. Conclusion:

E-tailing is a fast growing service in recent days. Rural people have more knowledge about

internet and they spend more or less equal time like urban people. In present days the rural

literate rate is increasing gradually. So, they have more knowledge about the e-commerce and

e-tailing. Today, farmers know new variety of seed and fertilizer from internet. The

Government provides more facility to learn updates in agriculture related information. Rural

people‘s expectations have increased not only in the e-tailing but also in all services. The

main problem of the rural people of Dharmapuri Dt., is using internet and visiting some

website they had compulsion to go browsing centre. The browsing centres are normally

charging Rs. 30 to 50 on hour// looks contradictory to your previous statement. Field and age

is a factor to determine the choices of spending time to related website expect music stores.

The e tailing service providers need to care about order confirmation and design area.


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***


“A STUDY OF EMOTIONAL INTELLIGENCE AT A PUBLIC SECTOR

UNIT IN BANGALORE”

Monica. M

Research Associate,

Acharya Institute of Technology,

Bangalore

Dr. L.Vijayashree

Associate Professor,

Department of MBA,

PES School of Engineering,

Hosur Road, Bangalore- 560100

Abstract:

Emotional intelligence refers to the ability to recognize and regulate emotions in ourselves

and others. Emotional Intelligence (EI) is considered to be a very powerful tool to an

employee to manage relationships and achieve success at work. The aim of this research was

to study the role of emotional intelligence among the employees at Karnataka State Remote

Sensing Application Centre (KSRSAC) and further this study investigates the relationships of

demographic factors (Gender, age, Education level, marital status and Income) and emotional

intelligence.

The census method was adopted which includes all 120 employees at KSRSAC as sample.

To assess the emotional intelligence, Researchers used Goleman’s method, which includes 25

questions. In addition, some personal and social demographic data was gathered from the

employees. Data were analyzed using SPSS-17 and descriptive and inferential statistics.

The study explores the relationship of factors of EI within and also concludes that when age

increases the social skills decreases. The result proves that the males have more EI compared

to females at KSRSAC but the variation among the gender groups is less.

KEY WORDS: Emotional intelligence, Self awareness, Self management, Self motivation,

Empathy and Social skills.


Introduction:

Emotional Intelligence (EI) refers to the ability to recognize and regulate emotions in

ourselves and others (Goleman, 2001). Peter Salovey and John Mayer, who originally used

the term "Emotional Intelligence" in published writing, initially defined emotional

intelligence as:

A form of intelligence that involves the ability to monitor one's own and others' feelings and

emotions, to discriminate among them and to use this information to guide one's thinking and

actions (Salovey & Mayer, 1990).

Evolution of EI:

Goleman: A Mixed Model of Emotional Intelligence

Daniel Goleman, a psychologist and science writer who has previously written on

brain and behavior research for the New York Times, discovered the work of Salovey and

Mayer in the 1990's. Inspired by their findings, he began to conduct his own research in the

area and eventually wrote Emotional Intelligence (1995), the landmark book which

familiarized both the public and private sectors with the idea of emotional intelligence.

Figure-1: HR Activity


Goleman identified the five 'domains' of EI as:

1) Self-awareness: Self awareness (SA) concentrates on one’s vision, values &

belief. SA examines one’s emotions towards their performance and helps in decision

making by using their values. SA also helps to identify one’s strength and weakness

& learn from experience, finally SA makes person to become more confident.

2) Self-management: Self management (SM) able to manage their stress by having

positive attitude towards self and also others. Self managed people try to control their

temper and able to perform under pressure and these persons can be trusted.

3) Self-Motivation: Self motivation (SMo) helps to increase the commitment in

work. Self Motivated people are capable to take initiative to achieve the goals by

taking up the new challenges at work place.

4) Empathy: Empathy (E) helps to understand the others behaviour and feeling and

they will be open in their thoughts and try to be aware of their culture and work

in diversified workforce. .

5) Social skills: Social skills (SS) indicate that people are capable of listening to

others and also communicate effectively. SS influence, lead others and manage

change and adapt to the situation by dealing with others emotions.

Figure-2: EI Components


Review of literature:

1. Michael Gosling (2006) explains in his PhD Thesis “Measuring emotional

intelligence of managers in Singapore and the application of emotional intelligence

for individual and organization effectiveness. An exploratory study” that male

respondents scored higher than did their female counterparts. And also proves that the

EI abilities were independent of age by considering 3 age groups.

2. Pandey Hari Shankar (2010) in his journal paper “Evaluating Characteristics &

Emotional Intelligence among workers in organizations in the state of Rajasthan”

investigated the relationship between demographic variables and emotional

intelligence among workers and shows the result that there was also significant

difference in the emotional intelligence mean scores of male and female.

3. Mary Jo Jackson and Sharon Larisa Segrest Research in Higher Education Journal

“The effects of emotional intelligence, age, work experience, and academic

performance” paper found that the emotional intelligence was found to be positively

associated with work experience and also emotional intelligence was not significantly

associated with age and academic achievement.

4. Souvik Ghosh and Suvarna Chakraborty (The Journal of Business Perspective l

Vol. 12 l No. 1 l January–March 2008) in their journal paper “Emotional intelligence:

the next step in knowledge process outsourcing” has done a comparative study

between two companies. And shows that there exists a relationship between efficient

synergistic determinants of emotional intelligence of knowledge employees and

sustained competitive edge. This is proved by the level of importance attached to

emotional intelligence in Company B where a more integrated and synergistic HR

strategy was able to adapt to the expectations of knowledge employees faster than

Company A. This journal paper also shows the importance of information sharing and

communication among collaborators and business partners to handle the emotions of

the employees better. And proves that flexible emotionally intelligent and mature

leadership helps achieve faster growth rate.

5. Blair Kidwell, David M. Hardesty, Brian R. Murtha, & Shibin Sheng (Journal of

Marketing Vol. 75 (January 2011),) in their research work “Emotional Intelligence

in Marketing Exchanges” examined how sales professionals use emotions in

marketing exchanges to facilitate positive outcomes for their firms, themselves, and

their customers. The authors conduct three field studies to examine the impact of EI in

marketing exchanges on sales performance and customer relationships. They find that

EI is positively related to performance and finally the results indicated a

complementary relationship between EI and cognitive ability in that EI positively

influences performance at higher levels of cognitive ability.

6. The Emotional Intelligence and Leadership Study was conducted by Dottie Brienza

(Consortium for Research on Emotional Intelligence in Organizations Leadership &

EI at J&J). In his research, results showed that the highest performing managers have

significantly more emotional competence than other managers. There was strong

inter-rater agreement among Supervisors, Peers, and Subordinates that the

competencies of Self-Confidence, Achievement Orientation, Initiative, Leadership,

Influence and Change Catalyst differentiate superior performers. The high potential

managers received higher scores in the emotional competencies by Peers and

Supervisors, but not by Subordinates. Some gender difference was found, with

Supervisors rating Females higher in Adaptability and Service Orientation, while

Peers rated Females higher on Emotional Self-Awareness, Conscientiousness,


Developing Others, Service Orientation, and Communication. Direct reports scored

Males higher in Change Catalyst.

7. Samuel O. Salami (2008) in his research paper “Demographic and Psychological

Factors Predicting Organizational Commitment among Industrial Workers”

investigated the relationships of demographic factors (age, marital status, gender, job

tenure, and educational level), emotional intelligence, work-role salience,

achievement motivation and job satisfaction to organizational commitment of

industrial workers.

8. Cary Cherniss Graduate School of Applied and Professional Psychology Rutgers

University” Emotional Intelligence: What it is and Why it Matters” Cary Cherniss,

Ph.D. October 7, 1998 Bringing Emotional Intelligence To The Workplace

The EI concept is a psychological one, it is important for I/O psychologists to

understand what it really means and to be aware of the research and theory on which

it is based. So in this presentation it brief about the history of the concept as an area of

research and describe how it has come to be defined and measured. The research links

emotional intelligence with important work-related outcomes such as individual

performance and organizational productivity.

9. Fabio Sala, Ph.D Consortium for Research on Emotional Intelligence in Organizations

EI Program Eval. “Do Programs Designed To Increase Emotional Intelligence At

Work?”

The recent and widespread interest in the importance of emotional intelligence (EI) at

work (Goleman, 1995) has led to the development of programs that are designed to

(1) educate people about the relevance of emotional intelligence in the workplace, (2)

assess their relative strengths and weaknesses, and (3) provide a framework to

develop and enhance their ability to interact with others with greater emotional

intelligence (Boyatzis, 1999). This research will attempt to provide some evidence for

the effectiveness of an emotional intelligence training program; specifically, whether

participants scores on a measure of EI improve after exposure to a program designed

to increase emotional intelligence at work. Increases in EI scores with both samples

suggest that workshop interventions are effective at improving EI

10. Kathleen Cavallo, PsyD, Corporate Consulting Group and Dottie Brienza, MA The

Emotional Intelligence and Leadership Study at J&J

A study was conducted on three hundred and fifty-eight Managers across the Johnson

&Johnson Consumer & Personal Care Group (JJC&PC Group) globally to assess if

there are specific leadership competencies that distinguish high performers from

average performers. Participants were randomly selected, then coded for performance

rating, potential code, gender, functional group and regional area. Results showed that

the highest performing managers have significantly more “emotional competence”

than other managers. There was strong inter-rater agreement among Supervisors,

Peers, and Subordinates that the competencies of Self-Confidence, Achievement

Orientation, Initiative, Leadership, Influence and Change Catalyst differentiate

superior performers. The high potential managers received higher scores in the

emotional competencies by Peers and Supervisors, but not by Subordinates. Some

gender difference was found, with Supervisors rating Females higher in Adaptability

and Service Orientation, while Peers rated. Females are higher on Emotional Self-

Awareness, Conscientiousness, Developing Others, Service Orientation, and

Communication. Direct reports scored Males higher in Change Catalyst.

11. Steven B. Wolff, DBA*November 205, Emotional Competence Inventory (ECI)


The ECI is a 360-degree tool designed to assess the emotional competencies of

individuals and organizations. It is based on emotional competencies identified by Dr.

Daniel Goleman in Working with Emotional Intelligence (1998), and on competencies

from Hay/McBer’s Generic Competency Dictionary (1996) as well as Dr. Richard

Boyatzis’s Self-Assessment Questionnaire (SAQ).ECI has shown strong evidence for

the assessment, development, and training of emotional intelligence. The Emotional

Competence Inventory 2.0 (ECI) measures 18 competencies organized into four

clusters:

Self-Awareness, Self-Management, Social Awareness, and Relationship Management

etc.The ECI is supported by very good reliability and validity evidence from research

from a variety of worldwide organizational contexts.

12. Samuel Olayinka Salami Ph.D., senior lecturer, head of Department of Guidance and

Counseling, Kampala International University; research fields: counseling

psychology, personnel psychology and career development - SEPTEMBER 2010,

“Gender as a moderator of relation between emotional intelligence and career

development”

The purpose of this study is to examine the relationship of emotional intelligence with

career development and the moderating role of gender in the relationship. This study

adopted a survey research design. Questionnaires were used to obtain data on

emotional intelligence, career development and demographic factors from 485

secondary school students (male=255, female=230) randomly selected from 5 states

in south western Nigeria. Data analysis included regressing career decision-making

self-efficacy and career maturity on emotional intelligence and gender. Results

indicated that emotional intelligence and gender predicted career development

and gender moderated the relationship between emotional intelligence and career

development. The implication of the findings is that counseling psychologists should

assess the emotional intelligence of the male and female students when conducting

career counseling. In addition, the findings suggest that the students need to be

exposed to counseling interventions for enhancing their emotional intelligence.

13. Hossein Namdar, Mohammad Sahebihagh, Hossein Ebrahimi, Azad Rahmani-2008

IJNMR Autumn 2008; Vol 13, No 4. “Assessing emotional intelligence and its

relationship with demographic factors of nursing students.”

The aim of this research was to assess the emotional intelligence of nursing students

and its relation with some personal and social. To assess the emotional intelligence,

the research has used BarOn EQ-i, which includes 90 questions in 5 categories and 15

scales scoring in a range between 90 and 450. In addition, some personal and social

demographic data were gathered from the students' educational files. Data were

analyzed using SPSS-13 and descriptive and inferential statistics. The students' mean

score of emotional intelligence was 332.08 ±39.08. The research shows that there was

no significant relation between emotional intelligence score and sex, education, and

students' interest in nursing. However, there was a significant relation between

emotional intelligence score and the students' satisfaction of their family socio-

economic status.

14. Mallika Dasgupta, Research Scholar, Department of Applied Psychology, University

of Calcutta “Emotional Intelligence emerging as a significant tool for Female

Information Technology professionals in managing role conflict and enhancing

quality of Work Life and Happiness” ASIAN JOURNAL OF MANAGEMENT

RESEARCH- 2010


Studying the role of Emotional Intelligence in managing Role Conflict and enhancing

Quality of Work Life and happiness among female IT Professionals, female IT

professionals have been found to be benefiting from their level of EI in achieving a

work family life balance and experiencing a higher Quality of Work Life and

experiencing an enhanced level of happiness. The research shows that that EI does

bear a negative relationship with Work Family Role Conflict and a positive

relationship with QWL and Happiness. the fact that Emotionally Intelligent people are

highly motivated and thus, meet their role demands without experiencing much stress.

15. Neerpal Rathi and Renu Rastogi, Journal of the Indian Academy of Applied

Psychology October 2009 “Assessing the Relationship between Emotional

Intelligence, Occupational Self-Efficacy and Organizational Commitment”

The purpose of this study is to explore the relationship among Emotional Intelligence

(EI), occupational self-efficacy, and organizational commitment. Data were collected

120 employees working in various organizations in India. A positive and significant

correlation is observed between EI and occupational self-efficacy (p< 0.01), whereas

a positive relationship (not significant) is observed between EI and organizational

commitment. Moreover, a low positive association is found between occupational

self-efficacy and organizational commitment. The research implies that EI and

occupational self-efficacy are related with a variety of organizationally desirable

outcomes. The results of this study indicate that EI significantly predicts occupational

self-efficacy in such a way that employees with a high level of EI exhibit a high level

of occupational self efficacy.

16. K.V.Petrides Adrian Furnham, Department of psychology, University college,

London, The Journal of social psychology 2004, “Estimates of Emotional and

Psychometric Intelligence: Evidence for Gender- Based Stereotypes”

The research has considered the hypothesis that men would give higher IQ but lower

EI self estimates than the women and that participant, regardless of gender would rate

their father as higher on IQ but lower on EI than their mothers. The result in this

research paper confirmed that the hypothesis view that people perceive psychometric

intelligence as a primarily masculine attribute in contrast with EI, which they perceive

as a primary feminine attribute. The result also showed that the intensity of the

stereotypical perception of 9 attribute diminished when the authors asked participants

to estimates their score.

Research Methodology Questionnaire method has adopted to collect data from the respondents. Descriptive

research was adopted for the sample size of 120. The data was collected from all the

120 employees in the given time frame at KSRSAC. Census survey was used to

collect data. Primary data was collected from the employees working at KSRSAC,

Bangalore, using well structured questionnaires. Likert scale was adopted in designing

the questionnaire & both open and closed ended questions were used. Secondary data

has collected from the company websites, journals, white papers etc.

The Objectives of the Study

The purpose of this study was to investigate the relationship of some demographic

factors (age, gender, education level, and Income) and emotional intelligence

The ability to manage feelings, generate confidence and trust among the workers

during the process of developing them in order to achieve the organization’s


objectives and goals is one of the other aspects of EI that has been found to be

important. In this context, the objectives are as follows.

1. To find relationship between the factors/dimension of EI.

2. To find relationship between the factors of EI and Demographic factors.

3. To find the impact of various demographic factor with EI Factors.

The following three hypotheses have been formulated for this study:

Hypothesis1: There is a significant relationship among the factors of EI

Hypothesis2: There is a significance relationship between the factors of EI and

Demographic factors

Hypothesis3: There is a variation among demographic factors and factors of EI

Analysis:

Objective1: “To find relationship between the factors of EI”

Hypothesis1: “There is a significant relationship among the factors of EI”

Result: Table 1: Correlations

Self

Awareness

Self

Management

Self

Motivation Empathy

Social

Skills

Self

Awareness

Pearson

Correlation 1 .044 .224

* .050 .117

Sig. (2-tailed) .630 .014 .588 .202

N 120 120 120 120 120

Self

Management

Pearson

Correlation .044 1 .331

** .114 .035

Sig. (2-tailed) .630 .000 .215 .703

N 120 120 120 120 120

Self

Motivation

Pearson

Correlation .224

* .331

** 1 .107 .102

Sig. (2-tailed) .014 .000 .244 .269

N 120 120 120 120 120

Empathy Pearson

Correlation .050 .114 .107 1 .169

Sig. (2-tailed) .588 .215 .244 .066

N 120 120 120 120 120

Social Skills Pearson

Correlation .117 .035 .102 .169 1

Sig. (2-tailed) .202 .703 .269 .066

N 120 120 120 120 120

*. Correlation is significant at the 0.05 level (2-tailed).

**.Correlation is significant at the 0.01 level (2-tailed).

From the above table: 1, There is a correlation between self awareness and self

motivation with significance level of 0.014 and correlation between self motivation

and self management with significance level 0.00

The 2 factors of EI are highly positively correlated. I.e. there is significance

relationship between self motivation and self management (0.00) and self awareness


and self motivation (0.014). The most of the factors are positively correlated with out

significance. The research proves that all the factors of emotional intelligence are

positively correlated with one another.

Self awareness and Self management are positively correlated with Self motivation,

this means once a person is fully aware of one’s own self and cam manage him/her,

and it increases the level of motivation inside the person too.

Social skills are positively significant correlated with empathy. The research proves

that if a person increases Social skills then viewing the problems of others in others

point also increases (Empathy). Refer the table no. 1, on the whole all the factors of

EI are positively to one another.

Objective2: “To find relationship between the factors of EI and Demographic

factors”

Hypothesis2: “There is a significance relationship between the factors of EI and

Demographic factors (Age and income)”

Result: Self awareness is negatively correlated with age and significantly positively

correlated with income. The result proves that when is less, KSRSAC employees have

more awareness level towards them self and when they grow old this awareness

decreases. The result proves that people might be fully aware of their strength and

weaknesses when they are old. In case of income, the result of the study proves that

when the income increases, self awareness significantly increases; the income factor

is associated with employees experience and gets more income. He/she needs to know

more about their strengths and weaknesses and also need to be self confident. The

research concludes that as the employees’ income increases there self confidence

increases and they will try to assess themselves by knowing their strengths and

weakness. This study proves the concept that income and self awareness are

positively correlated.

The Self management is positively correlated with age and income but with no

significance, likewise the result also shows that self motivation is positively correlated

with age and income but with no significance.

The empathy is negatively correlated with age but there is no significance and

empathy is positively correlated with income factor with no significance.

The social skill is negatively correlated with age with 5% level significance. The

result proves that as age increases the social skills among the employee’s decreases.

Aged persons have experience in their work life. So people try to learn from their

experience rather from others. The social skill is negatively correlated with income

with no significance. (Refer table no 2) This means that people with more age are less

communicative and they are not able to manage the changes and least bother about the

others emotions.

Table 2: Correlation

Correlation Age Income

Self Awareness--Pearson Correlation

Significance

-.130

.158

.205*

.025

Self Management--Pearson Correlation

Significance

.112

.223

.040

.664


Self Motivation--Pearson Correlation

Significance

.054

.560

.022

.812

Empathy --Pearson Correlation

Significance

-.073

.427

.030

.746

Social Skill--Pearson Correlation

Significance

-.158

.085

-.038

.684

*->Significant Correlation

Objective3: “To find the impact of various demographic factors (Gender, age,

Education qualification, marital status and Income) with the EI factors”

Hypothesis3: “There is a variation among demographic factors and factors of EI”

Result:

Self Awareness: Gender, education qualification level groups do not have variation

with respect to self awareness factors, in case if marital status there is a significant

variation across marital groups. This means between married, unmarried there is

variation when asked about self awareness. Usually married person have a control on

their emotions and examine their values when they need to take decision compared to

unmarried. This concept is proved here.

Self Management: Gender, education qualification level and marital groups do not

have variation with respect to self management factors. The levels of temper, being

positive, thinking capacity in pressure situation do not vary across the demographic

groups in KSRSAC.

Self Motivation: Between gender groups (male and female) there is no variation with

respect to self motivation, which means that both take up challenges equally and take

initiative, but in case of marital status, education level there is a no variation with

respect to self motivation (refer table 5) we can understand that married have more

self motivation than unmarried and widowed. This can be understood that married

face more challenges in their life that unmarried and widowed.

Table 7 shows that, UG employees have more self motivation that PG and others,

which proves that young people love to take up challenges and are optimistic in their

actions.

Empathy: There is significant variation between education level groups with

empathy factor (Refer table no: 3). between the education level (PG & above and UG)

there is a slight variation, which means the understanding about others is more for UG

people compared to PG & above people. There behaviours in the work place also vary

and cultural awareness will also have slight variation between PG& above and UG

groups which is also viewed in table no: 7

Social Skills: There is a significant variation between the education levels with that of

social skills factor (Refer table no: 3). which means that the variation is there in

communication and listening skills among the education levels. The conflict avoiding

and managing the changing situation will be more for UG compared to PG & above

employees at KSRSAC (Refer table no: 7)The UG employees are capable to work in

teams. And manage their emotions in group.

Table 3: Anova


Anova Gender Education level Marital status

Self Awareness – Sig

F- Value

0.240

1.392

0.401

0.922

0.002

6.502

Self management -- Sig

F- Value

0.496

0.466

0.140

2.001

0.515

0.668

Self motivation -- Sig

F- Value

0.867

0.028

0.028

3.672

0.013

4.473

Empathy -- Sig

F- Value

0.358

0.852

0.006

5.426

0.887

0.120

Social skills -- Sig

F- Value

0.320

0.995

0.038

3.357

0.620

0.480

Table 4: Mean and SD

Gender * Emptional intelligence factors

Gender:

Self

Awareness

Self

Management

Self

Motivation Empathy Social Skills

Female Mean 2.85 2.55 2.03 2.02 2.08

N 60 60 60 60 60

Std.

Deviation

.732 .622 .610 .676 .530

Male Mean 3.02 2.63 2.02 1.92 2.18

N 60 60 60 60 60

Std.

Deviation

.813 .712 .469 .497 .567

Total Mean 2.93 2.59 2.03 1.97 2.13

N 120 120 120 120 120

Std.

Deviation

.775 .667 .542 .593 .549

Table 5: Marital Status*emotional intelligence factors

Marital Status:

Self

Awareness

Self

Management

Self



Table 7: Educational Qualification*Emotional Intelligence factors

Educational qualification:

Self

Awareness

Self

Management

Self


PG&Above Mean 3.03 2.43 1.92 1.78 2.03

Std.

Deviation

.897 .603 .595 .479 .499

UG Mean 2.84 2.62 2.00 1.97 2.25

Std.

Deviation

.718 .724 .471 .470 .535

Findings

The research proves that all the factors of emotional intelligence are positively

correlated with or less significant

There is a significant relationship between the self awareness and the income factors,

this shows that higher the income more will be the self awareness.

The result proves that when there is increase in education level among the employees

of KSRSAC, then there is increase in the self management and empathy in them.

The result proves that the increase in the level of education increases the self

motivation, which makes employee to be committed to work and take initiative

without the supervision of others and will be achievement oriented, which is required

to improve the performance of the employees at KSRSAC.

The research concludes that the increase in the age decreases the social skills since the

aged persons try to learn from their experience.

The result proves that the males have more EI compared to females at KSRSAC but

the variation is among the gender groups is less.

Single Mean 3.08 2.55 2.00 1.95 2.14

Std. Deviation .777 .688 .527 .621 .585

Married Mean 2.76 2.64 2.11 2.00 2.11

Std. Deviation .679 .645 .532 .564 .487

Widowed Mean 1.50 3.00 1.00 2.00 2.50

Std. Deviation .707 .000 .000 .000 .707


There is no variation among the age groups and the factors of EI lie between the age

group of 20-35.

The increases in the income factor increase the factors of EI like self management,

self motivation and empathy.

Conclusion: Emotional Intelligence is more critical for employees at work place.

From the research, The research conclude that there is a positive correlation among

the factors of EI (Self management, motivation, awareness, social skills and empathy)

Gender: From the analysis, research concludes that there is a correlation between the

factors of EI and Gender. The research proves that the males have more EI compared

to females at KSRSAC. But the there is no much significant variation among the

gender groups and EI. The female can improve their EI by managing personal and

work life better. The male need to work on the few factors like self motivation and

empathy to improve overall EI and The female can improve their social skills by

interacting more with the colleagues and try to avoid shyness.

Age: There is a significant relationship between EI factors and age factor. From the

research, as the age increases the social skills decreases since aged people try to learn

from their experience rather than from others. So the social skills can be improved by

involving more in social gathering and team development activities. The research says

that the overall EI factors lie between the age group of 20-35 so the person above the

age of 35 can improve their EI by undergoing training on EI and involving in the team

development activities.

Education qualification: There is a significant relationship between the education

qualification and EI factors. The higher the education higher the self management,

self motivation and empathy. This gap can be filled by learning from the well

educated employees. The highly educated employees can give the feedback and

suggestions so that even less educated employees can improve the EI factors.

Suggestion:

• To Organization: The organization should arrange for maximum numbers of team

development activities in order to improve the social skills among the employees at

KSRSAC.

• The organization should adopt the two way communication by accepting the

suggestions and feedback from the employees.

• EI Training can be used to improve the EI among the employees.

• To Individuals: The individuals should be open minded and should be willing to

learn from others so that the empathy among the male employees will increases.

• Females should try to balance the work life.

• Females should interact more with colleagues, so that the social skills among them

can be improved.

• People should accept the feedback from the senior employees.

References:

Articles:

1. Cary Cherniss Graduate School of Applied and Professional Psychology Rutgers

University” Emotional Intelligence: What it is and Why it Matters” Cary Cherniss, Ph.D.

October 7, 1998, Bringing Emotional Intelligence To The Workplace.


2. Kathleen Cavallo, PsyD, Corporate Consulting Group and Dottie Brienza. “Emotional

Competence and Leadership Excellence at Johnson & Johnson” Consortium for Research on

Emotional Intelligence in Organizations Leadership & EI at J&J

3. Fabio Sala, Ph.D. “Do Programs Designed To Increase Emotional Intelligence At Work?”

Consortium for Research on Emotional Intelligence in Organizations EI Program Eval.

Reports: 1.Mike Gosling, “Measuring emotional intelligence of managers in Singapore and the

application of emotional intelligence for individual and organisation effectiveness”, an

exploratory study. PhD Thesis 2006. University of South Australia in 2006.

2. Steven B. Wolff, DBA*November 2005, “Emotional Competence Inventory (ECI)”

Technical Manual, Hay Group, McClelland Centre for Research and Innovation, Updated

November 2005.

3. Samuel Olayinka Salami, Ph.D., senior lecturer, head of Department of Guidance and

Counseling, Kampala International University; research fields: counseling psychology,

personnel psychology and career development.- SEPTEMBER 2010 US-China Education

Review, ISSN 1548-6613, USA, “Gender as a moderator of relation between emotional

intelligence and career development”

Journals: 1. Blair Kidwell, David M. Hardesty, Brian R. Murtha, & Shibin Sheng, “Emotional

Intelligence in Marketing Exchanges”. Journal of Marketing. Vol. 75 (January 2011).

2. Hossein Namdar, Mohammad Sahebihagh, Hossein Ebrahimi, Azad Rahmani-2008

“Assessing emotional intelligence and its relationship with demographic factors of nursing

students.” IJNMR Autumn 2008; Vol 13, No 4.

3. Pandey Hari Shankar. Evaluating Characteristics & Emotional Intelligence among Workers

In Organizations In The State Of Rajasthan. International Research Journal. July 2010.

4. Mary Jo Jackson and Sharon Larisa Segrest, “The effects of emotional intelligence, age,

work experience, and academic performance” Research in Higher Education Journal

5. Mallika Dasgupta, Research Scholar, Department of Applied Psychology, University of

Calcutta “Emotional Intelligence emerging as a significant tool for Female Information

Technology professionals in managing role conflict and enhancing quality of Work Life and

Happiness”. Asian journal of management research- 2010 .

6.Neerpal Rathi and Renu Rastogi, Journal of the Indian Academy of Applied Psychology

October- 2009. “Assessing the Relationship between Emotional Intelligence, Occupational

Self-Efficacy and Organizational Commitment”.

7. Petrides. K.V., Adrian Furnham, Department of psychology, University College, London

and G.Neil Martin, Department of psychology, Middlesex University, London, The Journal

of social psychology, “Estimates of Emotional and Psychometric Intelligence: Evidence for

Gender- Based Stereotypes” .

8. Samuel O. Salami. “Demographic and Psychological Factors Predicting Organizational

Commitment among Industrial Workers. 2008. Department of Guidance and Counselling,

University of Ibadan, Ibadan, Nigeria. Emotional Intelligence: The Next Step In Knowledge

Process Outsourcing”, The Journal of Business Perspective l Vol. 12 l No. 1 l January–March

2008.

***


PROFESSOR’S CHOICE: FACTORS EFFECTING PRE PURCHASE

BEHAVIOR OF PRIVATE HEALTH INSURANCE, AN EMPIRICAL

ANALYSIS

Soumik Gangopadhyay

Research Scholar

West Bengal State University

Dept. of Commerce and Management

Berunanpukuria, Malikapur, Barasat,

West Bengal, India, Pin- 700126

Abstract

With the increasing number of population of India, it has been predicted that 70% of them

will be confined to the urban setup. Acceleration of life style related diseases of urban society

is augmenting business opportunity for the private hospitals by leaps and bounds. Disease

pattern is showing a change by shifting its dimension from infectious to non-infectious

dominance in Indian urban society. A field survey has done on 300 faculties of 10 self-

financing colleges of West Bengal to identify the motivation of purchase of health insurance

products. The result is surprisingly indicating that accessibility and awareness have an

important role in the motivation process of choosing health insurance brands. The study also

explores an immense potentiality of Indian health insurance market with ample opportunity.


Introduction – Insurance is a reliable source of security, freedom from anxiety, fear and

peace of mind. For a premium, a person can avail medical and surgical services. Indian

insurance industry is becoming consumer driven and a timid response has initially been given

by Indian customers. With the changing need of customers perception regarding healthcare,

Indian insurance market is offering its different product through versatile packages.

Innovative offers are on the nail. Fundamentals of these are highlighting on return to

reciprocate investment. Lucrative income is highlighted to promote these brands. Indian

social structure has shown dramatic changes influenced by versatile reasons i.e.

industrialization, heterogeneous needs of people influenced by globalization, accelerated

disability/inability conditions created by life style related diseases are forcing people to

consistently increase the epistemic value of healthcare related products. People can feel the

impulse of pathetically unpredictable consequences performed by these diseases. They are

becoming paranoid regarding these situations. Hence a business avenue is being generated

and an incredible opportunity for the Indian insurance companies to explore their business

into a related dimension has incidentally happened. The urban Indian society is haunted by

fear of unknown lifestyle diseases, whose sudden attack silently creates short / long term

disability. However, health uncertainity (Death / permanent disability) is becoming an

affluent cause of motivation of investment in health insurance.

Health insurance, being a contract of health risk purports certain criticality to market it

among customers,

A. Structural weakness -

1. Intangible dimension of health insurance as a product is maximum. Health is a free product

as traditionally received by Indians. Health crisis is an emergency phenomenon as perceived

by people.

2. People can‟t foresee future. A single premium fails to cover all major arrays of disease.

3. People invest on the basis of current trend.

4. Doesn‟t offer least income opportunity. So the motivation of investment is poor.

5. Epistemic value is less.

6. Problems of growth as the competition are increasing.

7. Cost of service / clarity in cost of service as varied from one hospital to other.

8. Problems in innovation as the issue is delicate (life and death situation). People purchase

the product as generic not as a brand.

10. Difficulty in recognition of a good or poor quality service.

B. Operational weakness –

1. Absence of product differentiation due to various degree of offer.

2. Problem of describing the process of service. Difficulty in describing the content of a

service.

3. Clustered/diffused demand as customer can approach from any part.

4. Accelerating complexities of health related problems due to incorporation of newer

diseases.

5. Barriers of direct communication.

6. Restrictive regulations incorporate more difficulties to handle variation from one case with

the other.

C. Outcome weakness –


1. Difficulty in convincing the customer about the fairness of the price charged.

2. Hardship in controlling patient interface. Emergency help and feedback system respond

slowly.

3. Irregular service quality and absence of supervision of implementation of standards in

different hospitals.

4. Barriers of direct communication.

5. Due to poor knowledge associated with awareness it is difficult to define the justification

of complexities related to reimbursement.

Health insurance has been classified in two categories namely family floater‟s policy (family

coverage) and individual policy (single coverage). Some firms have differentiated their

brands on the basis of accessibility of number of hospital coverage, variation of premium on

number of diseases, tenure of insurance coverage.

In the early 1990s, the floodgate of liberalization & globalization was opened in India that

forces the economy in a competitive market. Hospital occupies 50 per cent of Indian

healthcare market, whereas, pharma, diagnostic, insurance and medical equipments holds 25

per cent, 10 per cent and 15 per cent respectively [6]. According to RNCOS – 2009, 70 per

cent of all hospitals and 40 per cent of beds in the country are controlled by the private sector.

Broadly speaking, 80-85% Indian hospital market is dominated by private investors (IBEF –

Oct, 2010). 75% of expenditure on healthcare in India is still being met by “out of pocket”

consumers. 10% of total indian population today has health insurance coverage [3]. Health

insurance coverage among urban, middle upper class indians, however is significantly higher

and stands at approximately 50%. IRDA (insurance regulatory development authority) is the

governing body responsible for promoting insurance business and introducing insurance

regulations in India. In 2001 the IRDA introduced provisions for Third Party Administrators

(TPA) to support the administration & management of health insurance products offered by

insurance companies. TPAs are facilitators in the coordination process between the health

insurance provider and the hospital.

Table 1 : Current trend of Indian health insurance market.

Indian health insurance market

2008-2009 2009-2010

Health Insurance as non-life insurance 6088 cr.(20.66%) 7311 cr. ( 21.12 %)

Standalone health insurance (premium ) 535.09 cr. 1072.08 cr.

Source: IRDA annual report 2009-10 (market share of the total insurance market)

Importance of the study - The prospect of this research was created based on the report of

Government of India-Ministry of health and family welfare September 2010, 42% of all

deaths of urban India are accountable for non communicable diseases compared to 38% for

communicable diseases. Rural India is showing a reverse scenario where 41% death is

communicable and 40% is responsible for non communicable diseases. These diseases don‟t

have any preventive therapy other than treatment. Sudden attacks of these diseases are

creating the crucial need of acute cashless hospitalization. Health insurance can function as

an important instrument to cope up the emergency attack of these lifestyle related diseases.

Objective of the study –

1. Pre purchase behavior of a group of faculties regarding the purchase of private health

insurance products.


2. To identify the factors influencing the motivation of purchase of private health

insurance products.

3. To specify the factors affecting the design of private health insurance products.

Survey of literature – Through different plethora of studies, it has been widely concurred by

different researchers that, need of healthy life varies with difference in demography,

mortality, crude birth rate and nutritional deficiency (WHO, 1998). Inequality in

affordability, imbalance in accessibility to quality healthcare and discrimination of health

expenditure are the vital reason that creates health inequality among different community of a

civilization [9]. Social factors like dissociation of family, isolated geriatrics etc. are

responsible for lifestyle related diseases which requires hospitalisation. With improved

literacy and better employment opportunities now available, many of the health problems

confronting the less developed countries have been erased. However, sedentary lifestyle an

overambitious outlook, excessively aggressive competition, lack of regular exercise,

excessive consumption of alcoholic beverages and smoking, etc., have brought

noncommunicable diseases like obesity, diabetes, hypertension, myocardial infarction, etc. to

the forefront. Similarly, mental health has also been compromised [5]. In West Bengal the

dominance of life style related diseases are dominating over infectious diseases [7].

Individual food, nutrient and dietary pattern affect the mortality related to cardiovascular

diseases and cancer [13]. Anyway, these diseases are creating a business dimension for the

healthcare market which is also an important reason of accelerating the private corporate

hospitals. Life style related diseases are more of personal choice rather than public health

[10]. People are now demanding for a better quality of life that are forcing the government to

get concerned about the quality of life of their people by reducing morbidity and mortality

[11]. Poor knowledge of health insurance and lack of knowledge regarding this are the main

causes of poor motivation of purchase of health insurance (HI). Knowledge of insurance and

awareness of benefit of health insurance is the effective influencer of health insurance

customer [8]. Awareness regarding health caused by disability influenced by physical ailment

is a hidden factor of motivation of purchasing HI products and perseverance of health is

better understood by chronically ill patients [12]. Bourne 2010 has shown that, old age group

purchase health insurance more than other age group as curative measures [2]. This is a

health risk averter instrument. Increased dependence on private healthcare, high level private

health expenditure, increased cost of out-of-pocket are creating extra financial burden on

Indian‟s shoulder [1, 4].

Research methodology - The whole study is based on the primary field survey data

collected from ten privately owned colleges located in different cities of West Bengal. In total

300 faculties (150 males and 150 females) were surveyed during July-September 2011 and

after screening of all the questionnaires, 289 filled up questionnaire have been finally used.

Health insurance motivation is a“5-Factor” model i.e. Accessibility, Awareness, Cost burden

(monetary costs & non-monetary costs such as searching cost, queuing cost, temporal loss,

risk of anxiety, loss of earning time etc.), Return on investment (ROI), Involuntary reasons.

The relationship between the customer interest and the „5-factors‟ such as Accessibility,

Awareness, Cost burden and Return on investment (ROI), Involuntary reasons can be

measured by the following model,

Y = a + b X1 + c X2 + d X3 + e X4 + f X5

Where, X1 = Accessibility


X2 = Awareness

X3 = Cost burden (cost which includes direct cost like doctor‟s fees, medicine cost,

additional investigation cost, travelling cost and other indirect cost like searching cost,

queuing cost, cost of temporal loss, cost of risk of anxiety and cost of loss of earning time).

X4 = Return on investment (ROI)

X5 = Involuntary reasons like previous experience, peers guidance etc.

Y= Motivation of investment in health insurance (HI) which is dichotomous qualitative

variable. i.e., Y=1 if the interested and 0, otherwise.

As the dependent variable is a binary variable we cannot apply OLS method to estimate the

model. A logit model is accordingly used to estimate the above model. Thus, the dependent

variable is binary taking a value of 1 for the interested respondent and 0, otherwise.

P = Probability that the customer will purchase a health insurance (HI).

All the statistical calculations have been done by using the computer software STATA.

Data analysis and interpretation – 81% males and 19% females out of 300 have health

insurance (90% cases are employer based scheme). Younger people, Person with chronic

illness are more prone to HI. Result emanated from the field survey has revealed that both the

gender doesn‟t symbolize Health insurance as status symbol and concurs about the poor

penetration of health insurance in the society they belong. Moreover, as a whole, faculties

observe health insurance as tax averter not as risk averter and consider this instrument as

savings option. Interestingly, male respondents prefer HI as a legitimate exchange of health

risk and money as they are more sufferers of degenerative diseases. The mass opinion

supports that paying premium should be a burden to be taken by the employers only.

Compared to males, females consider HI as cost burden. Overall the target audience has

given a mixed response regarding the approach of the health insurance companies that

indicates poor accessibility of this product. During designing, insurance companies must

design product separately fulfilling the versatile need of both male and female.

Present coverage of the market have targeted only the cream of the market i.e. people who

belong to the high income group and aware about the health insurance products. To grab

more market share, insurance companies have to design product that offers minimum

investment but maximum coverage of diseases through wide number of hospitals. By doing

so in the days to come, a price war will create between these companies who are required to

innovate their product by offering individual customer oriented service. Recent example is of

a mobile telephone service company who offer their customer just one call at zero balance.

Table : 3 Result of opinion of respondents on the basis of personal justification

% of Female respondents

(150)

% of Male respondents

(150)

Yes No Yes No

Health insurance is a symbol

of rich status

39 % 61 % 33 % 67 %

Health insurance poorly

penetrate our society

47 % 53 % 32 % 66 %

HI is a income tax averter

instrument

86 % 14 % 87 % 13 %

HI is a savings option 71 % 29 % 61 % 39 %

HI is a justified exchange of

health risk & money

26 % 74 % 64 % 36 %


HI premium mandatorily be

paid by employer

82 % 18 % 87 % 13 %

HI help to support a costly

treatment

79 % 21 % 78 % 22 %

HI company approached

during last 3 yeras

45 % 55 % 48 % 52 %

Health insurance is a cost

burden

87 % 13 % 60 % 40 %

Respondents with chronic

illness (Degenerative disease)

12 % 35 %

Monthly income status Rs. 10000-15000 – 10 %

Rs. 15001-25000 – 70 %

Rs. 25001 and above – 20 %

Rs. 10000-15000 – 17 %

Rs. 15001-25000 – 60 %

Rs. 25001 and above – 23

%

Age group 25-35 yrs – 23 %

36-45 yrs – 65 %

>46 - 12 %

25-35 yrs – 32 %

36-45 yrs – 43 %

>46 - 25 %

Source : Based on author‟s analysis as data received from field survey.

Table : 2 Logit analysis

Coefficient Std. Error t value Slope

(Evaluated at the

mean)

Constant -138.153 45.3764 -3.0446

Accessibility 2.52052 0.838913 3.0045 1.27699e-05

Cost Burden 2.34997 0.795974 2.9523 1.19058e-05

Awareness 2.31973 0.80964 2.8651 1.17526e-05

Involuntary 2.3025 0.834583 2.7589 1.16653e-05

ROI 2.1269 0.716116 2.9700 1.07756e-05

Source: Based on author‟s analysis using software STATA

Mean dependent var 0.790698 S.D. dependent var 5.07e-06

McFadden R-squared 0.821752 Adjusted R-squared 0.731092

Log-likelihood -11.79660 Akaike criterion 35.59321

Schwarz criterion 52.75208 Hannan-Quinn 42.56521

Likelihood ratio test: Chi-square(5) = 108.769 [0.0000]

All the independent variables have strong positive impact on the respondent‟s motivation.

McFadden's pseudo- R-squared = 0.821752 signifies that 82% of the dependent variable are

explained by the data which is highly significant. For all the factors such as treatment,

quality, care and cost, the p-value are tested at i.e., 10 per cent level of significance which

signifies that all the independent variables are statistically significant in explaining the

dependent variable, i.e., health insurance purchase motivation (MHI). As the coefficients of

all the explanatory variables are positive and statistically significant, it implies that

accessibility, cost burden, awareness, involuntary reason and Return on investment all play

significant role in satisfying a patient. The derived model is as follows,

MHI = - 138.153 + 2.520 *Accessibility + 2.349 *Cost burden + 2.319* Awareness + 2.302

*Involuntary reasons + 2.126 *ROI


Conclusion – The study indicates that there is a transition phase is happening as the

insurance market is showing a tradition of dimensional shift from customer market to

business market and hence, individual care is absolutely in need of the hour. Even in an urban

setup, for a group of educated people accessibility of health insurance is a big concern. Any

health insurance company can promote this problem as their opportunity area of business and

design their distribution system to reach maximum prospective customer. The result also

indicate that health support is still considered categorically as emergency product even by the

majority of educated people emanated from reluctance shown by the studied population.

Further it is a concern that respondents are also price sensitive as they are not confident about

the benefits featured by the product. Although, it is a matter of great dispute about the

intensity of accessibility to a value added product which can fulfill their demand adhering

with their perseverance. Being a highly intangible product, the brands offered to the

customers should be designed from customer‟s point of view not on the basis of profitability

to attract maximum customers and in that case premium charged can be decreased in quantity

which will further be beneficial as it will be affordable to a large group of people. But, only

garnishing the existing brands of health insurance will never give mileage to sustain in the

competitive market. Rather, customer friendly brands are more acceptable. It is a big

challenge for the insurance company to design a brand offers low premium but covering a

treatment for a large no of diseases and eventually it will cover maximum number of

prospective customer. Health insurance companies must design the advertisement of these

products that will provide a help line which is customer friendly and will provide ample

information. However, Health insurance is an acute solution of chronic health problem.

Reference –

[1] Berman P, Ahuja R, Bhandari L,2010, “The impoverishing effect of healthcare payments

in India: new methodology and findings”, Econ Polit Wkly 2010, 45(16),65-71.

[2] Bourne A, Paul,2010, “Modelling social determinants of self-evaluated health of poor

older people in a middle-income developing nation”,Journal of Biomedical Science and

Engineering,Vol.3(July),700-710.

[3] Gangopadhyay, Soumik and Ghosh, Bidyut,2011, “Factors Effecting Patient

SatisfactionIn Private Sector Hospitals: A Case Study Of West Bengal”, Indian Journal of

Commerce and Management Studies,Vol.2(6), 102-106.

[4] Garg CC, Karan AK,2009, “Reducing out-of-pocket expenditures to reduce poverty: a

disaggregated analysis at rural-urban and state level in India”, Health Policy Plan,

Vol.24(2),116-128.

[5] Gupta C M; Mahajan K. B,2005, “Textbook of Preventive and Social Medicine”, Jaypee

Brothers Medical Publishers (P) Ltd. New Delhi (Revised third reprint), pp-4-10.

[6] Hazarika, I, 2010, “Medical tourism: its potential impact on the health workforce and

health systems in India”, Health Policy and Planning, Vol.25(3),248-251.

[7] Hazra Jayati,1990, “The changing pattern of diseases in West Bengal, India”, Singapore

Journal of tropical geography,Vol. 10(2),144-159.

[8] Mohammed Shafiu; Sanmbo, N, Mohammad; Dong, Hengjin, 2011, “Understanding

client satisfaction with a health insurance scheme in Nigeria: factors and enrollees

experiences”, Health Research Policy and Systems, 9(1),20-27.

[9] Mukherjee, Subrata; Haddad Slim; Narayana, Delampady,2011, “Social class related

inequalities in household health expenditure and economic burden:evidence from Kerala,

south India”, International Journal for Equity in Health, 10(1),1-13.

[10] Okamoto Etsuji,2007, “Is health a right or an obligation”, International journal of

integrated care,Vol.7 (Jan-Mar),1-12.


[11] Park, K,2010, “Preventive and Social Medicine”, Banarasidas Bhanot Publishers,

Jabalpur, India, pp- 302-340.

[12] Rooijen Reitsma-van Margreet; Jong, D de, Judith; Rijken, Mieke,2011, “Regulated

competition in health care: Switching and barriers to switching in the Dutch health insurance

system”, BMC Health Services Research 2011, 11 (May),95-104.

[13] Tourlouki E, Matalas AL, Panagiotakos DB, (2009). “Dietary habits and cardiovascular

disease risk in middle-aged and elderly populations: A review of evidence”, Clinical

Interventions in Aging, Vol.4,319–330.

[14] WHO, (1998) “The world health report, 1998. Life in the 21st century”. A vision for all.

WHO, Geneva.

[15] http://www.ibef.org/industry/healthcare.aspx (accessed on 06.10,2011)

[16]http://www.irda.gov.in/ADMINCMS/cms/frmGeneral_Layout.aspx?page=PageNo984&f

lag=1&mid=Annual reports >> Annual reports of the Authority (accessed on 06.10,2011)

[17] http://www.ibef.org/artdispview.aspx?in=29&art_id=28453&cat_id=119&page=1

(accessed on 06.08.2010)

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06.08.2010)

***


Book Review --- 99 Thoughts of Ganesha

Mrs Deepali Nilesh Pulekar

Thakur Institute of Management Studies and Research

India

Every chapter of this book has a unique thread of thought for Shree Ganesha. The 99 meditations or

chapters written by the author are well researched and draws us more closure to our much beloved and

favorite God – Ganpati Bappa.

The chapters in this book are well crafted into categories of Creation, Family, Representations,

Stories, Symbols, Temples, Festivals, Rituals, Literature, History, Spread, Wisdom. The book is

descriptive and narrates the bifurcation of 99 meditations starting from creation of Ganesha through a

mythological puzzle. This mythological puzzle communicates the profound truth. The belief of

Ancient Hindus that wisdom should never be given rather has to be taken is well written. The

approaches to understand the Lord through gyan yoga, bhakti yoga and karma yoga is what we human

beings could adapt to when we get ourselves too lost in materialism and the rat race.

The idea of evolution of Ganesha and its birth talks about one being a hermit, or a household wherein

the former withdraws from life and latter faces life fearlessly is a lesson to be learned. The old long

story of how Vinayaka i.e. a child created without the help of man to Ganesha is still carved through

various acts too. Thus, Ganpati as is formerly known the head of ganas, the name so came up after he

was guarding the mother’s cave as she was taking bath.

There is another explanation to the birth of Ganesha which talks about how, he too was different than

his father which is why he was given the elephant head. Ganesha here marks the point when human

consciousness stops being indifferent and willingly engages with the material world. The

transformation of goddess Kali to Gauri. The life taking form and life giving form. Re birth of

Ganesha symbolizes harvest and prosperity. This birth also helps the celebration of India’s two

agricultural cycles rabi and the kharif in autumn. The mythological importance of northern direction

and the qualities of stability and stillness should be looked forward too.

This direction is also ruled by Lord Kubera who is the lord of treasurer. This direction was soughted

by Shiva to get the animal head for Lord Ganesha. The Ganesha’s human body and animal head

reminds us that we have the ability in ourselves to overpower the beast within us that is always afraid.

Lord Ganesha’s celebration is closely associated with wealth and fertility. That’s why he was closely

associated to Airavat, Lord Indra’s elephant. The author has explained the meaning of swastika i.e su

–asti which mean let good things happen. We follow the ritual of writing Shri on wedding cards, key

documents and contracts till date.

The meaning of Shri writing is wonderfully written down. The 99 chapter talks about 2 principles of

certainty and uncertainty. How? if one has to come out of uncertainty remember Ganesha for

acquisition of intellect and wealth and prosperity is very beautifully connected. The scared of the

sound Omkar and its explanation leaves in no doubts. The immediate connect of Ganesha’s feet which

were equal to sound a, Ganesha’s stomach which was equal to y and Ganesha’s head was equal to m.

The turning point of Parshuram’s harsh behaviour towards Ganesh when he guarded the door talks

about a behavioral change from angry warrior to a sage who meditates.

The story of the race between the 2 brothers Lord Ganesha and Karthikeya gives a good moral of

intellect over power. It also conveys the strong value based system that Shiv Parvati and the two sons

possessed. Though the race was won by Shri Ganesh his appreciation of brotherly love by naming

Karthikeya the winner was true spirit of brotherhood. The importance of offering prayers to Lord


Ganesha is highly notified through the incidence when Vyas muni was entangled in his thoughts of

writing the Great Epic of Maharabharat. He was advised to offer prayers to Lord Ganesha and invoke

him for his blessings.

The history, segment, of the book talks about the widespread meteoric rise and increase in

worshippers of Ganesha. The 19th century Ganesh Upanishad has talked about Ganesha being

Syambhu. The other highlight in this segment is that Ganpati is the title that comes in the most of the

Vedas and Hindu Epic.

The analysis done by the author in the segment of wisdom gives us a room to raise appreciate inquiry

about the 2 forms of Ganesha The act of analysis where one focuses on the parts is called Shankya.

The act of analysis where one focuses on the whole is called Yoga.

Morya Gosavi played a key role in making Lord Ganesha a popular god of everyone. In fact,Ganpati

Bappa Morya has evolved after his name. The popularity of Ganesha was very well uphelded by the

Maratha dominance.

The book talks about how one can then finally draw a learning between Shankya – were one starts

recognizing what one actually is and what one is actually not.

***


INVESTOR ATTITUDE ON RISK AND INVESTMENT GOALS

AMONG EXPATRIATE - INDIANS IN OMAN

MOHAMED RAFIQ

Lecturer in Accounts & Finance

Business Studies Department

Nizwa College of Technology

Nizwa Sultanate of Oman

Abstract

The study is exploratory and empirical in nature attempts to understand the mobilization of

savings and levering of the Investment among the expatriates in a multi-cultural environment

like the Oman, utilizing the results of an attitude survey, analyses the motivations of

Expatriate-investors and their attitudes in the participation across a range of the investment

initiatives. It examines the influence of investment education and investment knowledge

in the pattern of their Investment. By using statistical tools the study attempts to evaluate the

association between variables such as investment goals, investor willingness to take risk,

attitude towards Investment portfolio construction etc.

Key words: Investor attitude, Investment goals, risk taking attitude and Investment stress


1.1 Introduction

The present study attempts to understand Mobilization of savings and levering of the

Investment among the Expatriates in a multi-cultural environment like the Oman, utilizing

the results of an attitude survey, analyses the motivations of Expatriate-investors and their

attitudes in the participation across a range of the investment initiatives, enables us to gain an

enhanced understanding of how an individual investor uses Investment education to make

useful Investment decisions. The study also covers the Investor stress, factors causing the

same, attitude over the alternate investment opportunities, the market cycle, reasons for

holding an investment portfolio etc., among expatriate investors in Oman.

2.1. Statement of the Problem

Most of the expatriates in Oman have financial goals but not many of them know how to go

about achieving the same. They lack investment knowledge or expertise to design an

investment plan that maximizes their savings. Consequently, they adopt the default approach

of leaving all the savings in bank deposits. This results in an asset allocation decision, one

that is very conservative. This conservative investment plan is simply not working as the

savings are not compounding fast enough to keep up with inflation. The investor need to

invest more wisely so that the savings earn sufficient returns to pay for essentials, holiday

trips, as well as their retirement plans.

2.1.1 Research Objectives

The specific objectives of this study are listed below:

1. To understand and review the existing literature on the significance of Investor

attitude, factors influencing the attitudes, investment stress and Investor risk taking

behaviour etc.,

2. To study the investor attitude among expatriate investor in Oman and examine the

factors influencing the same.

3. To examine the individual investors’ Investment education and Investment knowledge

in deciding their pattern of Investment.

2.2 Methodology

The study is exploratory and empirical in nature; primary data have been employed for the

study. The study consists of 50 samples, which are collected from the investors in Oman. The

data set include, primary data were collected through a method using structured questionnaire

and secondary data was collected from relevant publications and websites. The data collected

was converted into readable data and was tabulated and analyzed for logical status using

Microsoft-Excel spread-sheets and other appropriate statistical method. In this study, Chi-

square test has been employed to interpret. Suitable hypothesis framed and analyzed to

predict the preference of the investors.

2.2.1 Hypothesis of the study

Hypotheses are set for Chi-square analysis to check whether there was any association

between variables. The variables identified for analysis include; investment goals, investor

willingness to take risk, attitude towards Investment portfolio construction etc.


2.2.2 Data collection

Duration of 6 months was spent for the completion of the research topic and research activity,

carried out mainly in the city of Muscat, Oman among Indian expatriates. This period was

directed towards data gathering and analysis, as well as towards the drafting of reports on the

various phases of the research. The researcher selected samples to represent all segments in

the data. Keeping this fact in view, after identifying the factors influencing the attitude, a

questionnaire was prepared and it was pre tested and necessary modifications were

incorporated in the final draft which was administered for the collection of primary data. By

virtue of data obtained from the research survey, descriptive and analytical tests were carried

out.

2.2.3 Statistical Tools

The questionnaires are entered, verified, and edited using Microsoft-Excel spread-sheets.

Completed questionnaires were analyzed and the tests were calculated by using Microsoft-

Excel 2007 version as the tools of the study. Further, the chi-square test has been employed to

test the relationship between the socio-economic background and the level of attitude of the

respondents.

2.3 Positive and Negative Investor Attitude

An investor with a positive (optimistic) attitude is more likely to make money than one with a

negative (pessimistic) attitude.

Investor with an optimistic attitude

Realizes that not all choices are winners, that over the long run, with patience and

discipline, he will make money.

Sets aside his pride and let’s himself learn valuable investing lessons.

Understands that everyone makes mistakes, including himself and realizes that if you

learn from a mistake, it can be a good thing.

More likely to make money, given the same recommendations than someone who has

a negative attitude.

Likely to be happy at the end of each day, and more likely to start investing with a

positive attitude the next day.

Investor with a pessimistic attitude

Is more likely to give up hope and abandon a successful system and emotions,

More likely to focus on bad investments rather than good ones.

He is more likely to think he is always right, rather than others.

More likely to lose money, given the same recommendations than someone who has a

positive attitude.

More likely to be mad or upset or stressed out at the end of the day and more likely to

bring that back the next morning.

These cycles continue on and on and on...

That is why most successful people are optimists and most unsuccessful people are

pessimists. Investors must learn the value of this quality and always look on the bright side of

life!

2.4 Factors influencing Investment attitude

Everyone experience setbacks from time to time with his/her investments. Sometimes these

setbacks can put one down to the point that one loses the confidence in his/her ability to make

sound investment decisions.

Following factors influence investment attitude and contribute to regain investor confidence

http://stockinvestingsimplified.com/2011/seven-tips-to-improving-your-investment-attitude

http://www.greekshares.com/persist.php

http://www.greekshares.com/discipline.php

http://www.greekshares.com/mistakes.php

http://www.greekshares.com/advice.php


1. Taking full responsibility for one’s own investment decisions and avoid making excuses or

justifying one’s actions is the most important attitude expected of a successful investor.

Excuses are indicators of hidden fears and some time prevent the investor from looking out

for such cases where some one else successfully overcome the situation that the investor is

using as an excuse.

2. Investors must be in the group of associates with positive investment attitude. In doing so,

they develop the supportive habits that attract abundance into your life. Building an excellent

support network of like-minded investors who share a similar investment philosophy or

approach is very essential for positive investment attitude.

3. Investor must focus on what he can change in the moment, not on what has already passed

or could happen in the future. Live your life to the fullest in joy and gratitude one day at a

time. Life should be fun and so should investing.

4. Investor must be busy in stress releasing activities every day, whether physical or mental.

Relieving stress has a positive impact on both mental and physical health. It clears ones’

mind, facilitate better investment decisions.

5. Investor must take positive steps towards changing his/her attitude. Actions speak louder

than words. Identify and focus on those actions that bring about increasing confidence in

his/her abilities. In addition to reading the stock investment book that help improve one’s

investment knowledge, spending more time researching potential stocks gives greater

confidence to his/her investing abilities.

6. Investor ability to learn from failures determines whether or not he will become successful.

He must not take his/her failures personally and let him/her down.

7. Establish short-term goals that one can accomplish within a week or month. Consider goals

that entail networking online more with other investors, finding and connecting with a

mentor, or checking out an investment course to improve a specific gap in one’s investment

knowledge.

Once becoming more confident and better investor, the success stories of investment

continues

2.5 Leveraging the stress of investment

Inevitably people tend to get caught up in the potential returns of an investment and forget to

assess how to deal with the downside risk. And more often than not the problem stems from

their failure to understand the essence of what they are investing in and whether managing

such a strategy would suit their personality, their lifestyle and their risk profile. However this

could and is unnecessary and completely avoidable.

If people actually considered an investment from the point of whether they have the right

equity, time, experience, tenacity or knowledge to learn and manage the investment, then

most investors will find themselves thriving towards their dreams. On top of this in many

cases a poorly structured finance facility adds to a person's problems because they're unable

to gain access to more equity or exit earlier than expected incurring prohibitive costs and

penalties.

In most cases its just time that they need to buy for the situation to remedy itself and well

structured lending facilities will do this provided allowances have been made when the loan

was first established. Experiencing a loss through investment foul, causes a person's

confidence to be shot to shreds so severely that they may never attempt investing again of any

type, all because they were not given the right advice and information.

The road to financial freedom is filled with many lessons to learn so knowing what type of

investment suits you and your personality and having the right lending structure in place, will


not only save you a great deal of heartache, it will enhance your life the way investing is

intended to.

Individuals have different risk tolerances. Investor risk tolerance is the ability and

willingness to assume risk. Ability to assume risk is based on Investor’s chosen asset base,

investment time horizon, and his/her liquidity needs. In other words, investor’s ability to take

investment risks is limited by how much he/she have to invest, how long to invest it, and their

need for portfolio to provide cash—for use rather than reinvestment—in the meantime. Also

willingness to take risk is shaped by his/her ―personality,‖ investment experiences,

knowledge and education. Attitudes are shaped by life experiences, and attitudes toward risk

are no different. Figure 2.5.1, ―Risk Tolerance‖ shows how investor level of risk tolerance

develops.

Figure 2.5.1. Risk Tolerance

3.1 Review of Literature

Before undertaking the study on the motivations of Omani-Expatriate investors, an

exhaustive review of existing literature on the analysis of investor attitudes, in the

participation across a range of urban investment initiatives, enables us to gain an enhanced

understanding of how an individual investor uses information contained in analyst and

management forecasts, reasons for holding an urban regeneration investment portfolio,

evaluate factors and perspectives concerning the attraction of private finance into urban

investment.

In their study, Dhar & Zhu (2006) used investor trading records to investigate individual

differences in the disposition effect. They found that a fifth of the sample exhibited behavior

contrary to the disposition effect. They attributed this to investors' information quality and

ability to analytically process information. Interestingly they found that wealthier, older and

professional investors exhibited less of the disposition effect. They also found that trading


experience reduced the tendency for investors to commit the disposition effect. Individual

behavioral examination of methods to alleviate the disposition effect is a new direction in the

literature. Krishnan & Booker (2002) observed the characteristics which influenced investor

decision making when using analyst recommendations to make a short-term decision to hold

or sell a stock. They found that the 'strength' of the forecasts, which was determined by the

level of detail in the forecast, was a contributing factor in reducing the disposition effect.

When a weak analyst forecast was provided (i.e. no supporting information was provided to

support the analyst recommendation), it was found that it reduced the disposition effect for

gains, but it had no impact on losses. However, when an analyst forecast was strong, it

reduced the disposition effect for both gains and losses. Krishnan &Booker found that

investors had a tendency for regret aversion' consistent with Shefrin & Statman (1985). In

this respect, investors preferred to follow the analysts' recommendations rather than to do the

opposite. This was especially apparent for the strong analyst recommendations for a paper

loss, which is also consistent with loss aversion theory (Odean 1998) where investors were

reluctant to realize their losses. Krishnan & Booker (2002) is significant because it examines

a plausible solution to reduce the disposition effect with the use of detailed analyst forecasts.

More recently, the interrelationship between disclosures provided by management and

analysts has received considerable attention where the latter have been labeled as

accomplices in management's earnings guidance in situations where they have been

manipulated by management in their effort to improve perceived performance (Mittendorf

&Zhang 2005).The central theme of attribution theory is that individuals 'interpret behavior

in terms of its causes and that these interpretations play an important role in determining

reactions to the behavior' (Kelley & Michaela 1980, p. 458). We draw on this framework to

explain our prediction that news that is contrary to investors' expectations will have a greater

influence on their decisions.

Consumer behavior research began in the 1960s but there have been few studies on consumer

decision-making under risk about financial service industry. Financial products investors

often purchase investment products by drawing on experience or through the investment

appraisal process (Harrison, 2003). Therefore, past investment experience and expertise of

investors provides them with risk awareness and so have become important commodity risk

assessment factors in future. Some personal traits such as risk preference, and personal

experience affect risk assessment and awareness.

The propensity to build up risk can further affect actual behavior, where risk refers to how far

decision makers are prepared to extend their exposure to risk . Risk perception forms the

basis of risk communication which means that people facing uncertainty and ambiguity in the

available information, construct inferences and draw conclusions for them. These faculties

determine people’s attitude to risk and their behavior in risk related decisions. Risk

perception is determined from the questions investors ask, their familiarity with

organizational and management systems etc. all of which are important factors. Risk

perception and propensity to risk have a strong negative correlation. In fact, prospect theory

does not deal with the effects of past investor experience on future investment behavior.

Sitkin and Pablo (1992) developed a model of determinants of risk behavior. In this model,

personal risk preferences and past experiences form an important risk factor in which to

frame the problem, and social influence also affects the individual’s perception. Sitkin and

Weingart (1995) extend the Sitkin-Pablo model leading to the definition that risk perception

and propensity are the mediators in risk behaviours of uncertainty decision-making. In this


hypothesis, past investment establishes the frame for the propensity to risk, risk transfer, and

risk awareness which impact decision-making behaviour. Thus risk orientation and risk

perception are reduced to antecedent variables in decision-making behaviour under risk.

Investment experience is an important factor influencing behaviour. Investors with more

experience have relatively high risk tolerance and they construct portfolios of higher risk

(Corter and Chen, 2006). The success or failure of past investor experience influences the

tendencies of investors towards risk and risk perception, and further affects decision-making

behaviour. Kathleen Byrne (2005) shows that risk and investment experience tend to indicate

a positive correlation and past experience of successful investment increases investor

tolerance of risk. Inversely, unsuccessful past experience leads to reduced tolerance to risk.

Therefore past investment behaviour affects future investment behaviour.

The impact of behavioural differences by gender is also an important variable. Female

investors more of often than their male counterparts tend towards risk aversion which is

demonstrated by their more conservative investment behaviour. This claim is evidenced by a

smaller number of market enquiries, lower trading volume and lower frequency of

transactions attributable to females (Fellner and Maciejovsky, 2007). Ronay and Kim (2006)

have pointed out that there is no difference in risk attitude between individuals of different

gender, but between groups of such, males indicate a stronger inclination to risk tolerance.

That is, no gender difference was found at an individual level, but in groups, males expressed

a stronger pro-risk position than females.

Investor perception of risk affects the expected return on investment. In traditional concepts

of finance, it is understood that investors do not welcome risk but that investments with

higher expected rates of return are also understood to bear higher levels of risk. Thus risk and

reward are in positive correlation. However, not all investors possess this knowledge. Despite

a wealth of literature and trained professional opinion supporting the existence of a positive

correlation between risk and return, some novice traders and unskilled investors perceive

expected return to be in negative correlation to risk (Muradoglu, 2005) (Byrne, 2005).

Despite risk perception and the tendency of such to be transmitted and influence the decision

making behaviour, people continue to make investments in the face of uncertainty. This

decision making under risk is reflected in the individual investor’s portfolio construction.

That is, risk perception affects return expectations and asset allocation behaviour

simultaneously. Therefore the expected utility theory based on a traditional finance

perspective cannot explain the anomalous investment behavior of irrational people. Since this

incongruity was noticed, Kahneman and Tversky have proposed prospect theory as a

reasoned theoretical explanation for this phenomenon.

Normal investors are affected by cognitive bias and emotions in decision-making behaviours,

rational investors are not (Statman, 2005). Behavioural Finance scholars have already proven

that the act of engaging in risky decision-making in uncertain circumstances cannot be

considered ―rational‖ and that this descriptor should best be replaced with the more

appropriate ―heuristic‖ in that such decisions are by rule of thumb (they are experience

based). Thus decision-making in such circumstances may be understood without cognitive

bias. Heuristics is an important feature of the individual decision-making process which may

be considered to include thought representativeness heuristics (Tverversky and Kahnemen,

1972, 1973, 1974 and 1982) and availability heuristics (Tversky and Kahneman, 1973 and


1979). It is important here to understand that there is anchoring bias in the decision-making

process which arises due to factors such as overconfidence, loss aversion, status quo bias,

mental accounting, framing and so on. Investors in the process of assessing the risks and

returns are influenced by this anchor effect (Tversky and Kahneman, 1974). Kahneman and

Tversky claim that in the process of assessment, people use certain starting values as

reference points, and that these reference points may be volatile values to which subjects add

necessary adjustments. The KT experiment demonstrates that this adjustment is usually not

reliable and people confronted with different situations produce different anchor values.

Perceptions of risk are affected by anchors, which lead investors to raise their returns

expectations when given a bias/anchor of a higher value.

Behaviour Finance scholars believe in objective consideration of investment risk and return

because these factors can be strongly impacted by subjective framing influences. Decision-

making processes relying on frames often cause problems to be viewed in different ways,

which leads to different choices. Investors in financial markets receive a spectrum of reports

which can be interpreted differently making cognition a factor in the final decision-making

response. Shefrin and Statman (1994) found that noise traders have a greater cognitive bias

than informed traders.

Overconfidence and optimism are further forms of bias. De Bondt (1993) found that

individuals rely on their personal past experience as a foundation and it is from this that

excessive self-confidence in decision-making can originate. Such investors make

inappropriate decisions with insufficient information due to this personal trait (Shefrin and

Statman, 1994). In addition to Overconfidence bias, optimism is an Achilles heel leading to

investment losses. Individuals with this failing often feel they possess an innate talent and in

their optimism, over-rate their own assessment ability (Kahneman and Riepe, 1998). Having

overconfidence and optimism causes people to further overestimate their own knowledge,

underestimate risk, and it even reduces risk recognition.

4.1 Analysis and Interpretation

The data set include, primary data were collected through a method using structured

questionnaire. The respondents include 50 Oman based Indian expatriates of whom 30 were

male and 20 female. The respondents were questioned for their opinion on Investment habit,

saving pattern, period/frequency of investment, preferred investment areas, knowledge of

investments perception on Risk and Return, attitude towards Risk etc.,

The major findings include:-

Investment Knowledge:-

62% of the respondents agreed to have limited to nil knowledge of investment. More

than 50% of the male respondents possess limited to nil knowledge of investment.

28% of the female and 18% of the male respondents with less than AED 5000

monthly income possess limited to nil knowledge of investment.26% of the male and

12% of the female respondents possess good/extensive knowledge of investment.

Investment Goals:-

44% of the respondents have Inflation protection as their investment goal, followed

by significant growth of capital (24%) /capital preservation (20%).Only 12% of the

respondents preferred aggressive growth as their investment goal. Investor with


aggressive growth as their investment goal has Islamic securities /national bonds

/structured products as preferred areas of investment.

Investor risk taking nature:-

82% of the respondents were either average risk takers or low risk takers. 18% of the

respondents who were high risk takers have their investment goals evenly distributed

between - Aggressive growth, Capital preservation, Inflation protection and Sig.

growth of capital. Inflation protection was the most common investment goal among

all categories of risk takers.

Investor attitude:-

66% of the respondents – (42% male and 24% female) were having ―aggressive

investor attitude‖ whereby they would feel worse -Being in the stock market and

seeing their account go down substantially in value.34% of the respondents – (18%

male and 16% female) were having ―conservative investor attitude‖ whereby they

would feel worse - Not being in the stock market and seeing it (index) go up

substantially in value. Of the respondents -60% with average-to-low risk taking nature

were having ―aggressive investor attitude‖ whereby they would feel worse -Being in

the stock market and seeing their account go down substantially in value.

Investor expected return on investment:-

64% of the respondents were expecting return in less than 1 year; out of which 52%

were averages to low risk takers and 12% were high risk takers. 36% of the

respondents were expecting return only after 1 year; out of which 30% were averages

to low risk takers and 6% were high risk takers. Over all only 2 % of the respondents

were expecting return within 3 months and none of the female respondents were

expecting return within 3 months. Maximum number of respondents (62%) had

expected return in 6-12 months. Maximum number of respondents (82%) was either

low or average risk takers.

4.2 Hypothesis testing

Hypotheses are set for Chi-square analysis to check whether there was any association

between the variables investment objectives, investor willingness to take risk, attitude

towards Investment portfolio construction etc

1. Testing for association between investment goals and Risk taking categories of the

respondents: - (Ref: Annexure Table-1)

Null HO: There is no significant association between investment goals and Risk taking

category of the investors.

Alternative HO: There is significant association between investment goals and Risk taking


Table-1 showing investment goals and Risk taking categories of the respondents

Risk taking category

\ Investment Goals

Average risk

taker

High risk

taker

Low risk

taker

Grand

Total

Aggressive growth 3 2 1 6

Capital preservation 4 2 4 10

Inflation protection 11 2 9 22

Significant growth of

capital 3 3 6 12

Grand Total 21 9 20 50


Chi Square Statistic χ2 Absolute Values= 5.9382, Degree of Freedom= 6.

Table value @ 95% confidence (for 6 degrees of freedom) = 12.59.

The calculated chi-square value, 5.9382 is lower than the critical value at 0.05 and 0.01

significant levels. Hence, we accept the NULL hypothesis and conclude that there is no

relationship between investment goals and Risk taking category of the investors.

2. Testing for association between investment attitude and Risk taking categories of the

respondents Ref: Annexure Table-2)

Null HO: There is no significant association between investment attitude and Risk taking


Alternative HO: There is significant association between investment attitude and Risk taking


Table-2 showing investment attitude and Risk taking categories of the respondents

Investment

attitude\ Risk

taking category

Being in the stock

market and seeing my

account go down

substantially in value.

Not being in the stock

market and seeing it

(index) go up

substantially in value Grand Total

Average risk taker 14 7 21

High risk taker 3 6 9

Low risk taker 16 4 20

Grand Total 33 17 50

Chi Square Statistic χ2 Absolute Values=6.0309.Degree of Freedom= 2

Table value @ 95% confidence (for2 degrees of freedom) = 5.99147.

The calculated chi-square value, 6.0309 is higher than the critical value at 0.05

significant levels. Hence, we reject the NULL hypothesis and conclude that there is a

significant relationship between investment attitude and Risk taking category of the

investors.

3. Testing for association between education and investment knowledge and Risk taking

categories of the respondents Ref: Annexure Table-3)

Null HO: There is no significant association between Education and Investment knowledge

of the investors.

Alternative HO: There is significant association between Education and Investment

knowledge of the investors.

Table-3 showing associate Relationship exist between Education and Investment

knowledge

Investment knowledge

Education Extensive Good Limited None

Grand

Total

Graduate 3 8 7 5 23

Post Graduate & Above 2 6 15 4 27

Grand Total 5 14 22 9 50

Chi Square Statistic χ2 Absolute Values=3.21. Degree of Freedom=3

Table value @ 95% confidence (for 3 degrees of freedom) =7.8147.

The calculated chi-square value, 3.21 is lower than the critical value at 0.05 and 0.01

significant levels. Hence, we accept the NULL hypothesis and conclude that there is no

relationship between Education and investment knowledge of the investors.


5.0 Conclusion

Positive attitude enhances the capabilities of Investors. They are able to focus on

opportunities, not obstacles, and are persistent in finding solutions to investment challenges.

Most of the investments of Omani-Expatriates involve investments that are completely

unsuited to them. The reason being is that executives investing in property, stock or

derivative strategies that require a degree of diligence that becomes completely

unmanageable when combined with the day to day demands of their careers. Consequently

they make hasty decisions or fail to act when required and lose significant proportions of

their portfolios. The survey analysis had given clear conclusions that because of the

expatriate investors have limited to nil knowledge of investment and they have Inflation

protection followed by significant growth of capital and capital preservation as their

investment goal and no other aggressive investment goals they can aim at. This was justified

by the fact that 82% of the respondents were either average risk takers or low risk takers. The

age-old fact that that Education coupled with investment knowledge are the essential factors

decides the investment attitude of any Investor, was proved correct once again in the study.

BIBLIOGRAPHY

Web-sites visited:-

1. http://realbusiness.co.uk/news/investor-confidence-on-the-rise

2. http://www.todayonline.com/Commentary/EDC111203-0000040/Charting-your-

financial-goals

3. http://stockinvestingsimplified.com/2011/seven-tips-to-improving-your-investment-

attitude

4. http://www.greekshares.com/pessimistic_optimistic.php

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http://www.todayonline.com/Commentary/EDC111203-0000040/Charting-your-financial-goals

http://www.todayonline.com/Commentary/EDC111203-0000040/Charting-your-financial-goals



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***

Volume:01, Number:03, Jan-2012 : RJCBS Page 51

www.theinternationaljournal.org

TECHNICAL ANALYSIS OF SELECTED INDIAN BANKS

N R Benjamin Franklin

Faculty of Management,

EBET Group of Institutions

India

Abstract

This paper describes about the use of Technical Analysis for traders while taking buying and

selling decisions with the technical analysis done for the stocks of few selected Indian Banks.

Technical analysis is the most useful and consistent approach to trading in the markets.

Simply put, Technical analysis is the art and science of putting stock information on a chart

in the form of various kinds of bars and detecting different patterns indicators tosses the

market direction. While a lot of people know a least a little about technical analysis, very few

really know how to use it. Technical analysis is not an astrological science for predicting

prices and market direction. The main function of technical analysis is to show the current

demand-supply position of the market, or the particular stock, define risk and reward of each

particular trade, Technical analysis is not an end in itself; the end is its effective use for

profitable trading



TECHNICAL ANALYSIS

Technical analysis is the most useful and consistent approach to trading in the markets.

Simply put, Technical analysis is the art and science of putting stock information on a chart

in the form of various kinds of bars and detecting different patterns indicators tosses the

market direction.

While a lot of people know a least a little about technical analysis, very few really know how

to use it. Technical analysis is not an astrological science for predicting prices and market

direction. The main function of technical analysis is to show the current demand-supply

position of the market, or the particular stock, define risk and reward of each particular trade,

Technical analysis is not an end in itself; the end is its effective use for profitable trading.

CHARTS

Charts are the working tools of the analyst. They have been developed in a multitude of

forms and style to represent graphically almost anything and everything that take places in

the market, or to plot an “index” derived there form. They may be monthly charts on which

an entire month’s trading record is condensed into a singles entry, or weekly, daily, hourly,

transaction,” point and figure” candlestick etc.

They may be constructed an arithmetic, logarithmic, or square-root scale, or projected as

“oscillators” they may delineate moving averages, proportion of trading volume to prices

movement, averages price of “most active” issues odd-lot transactions the short interest and

an infinitude of others relations, ratios, and indexes-all technically in the sense that they are

derived, directly or indirectly, forms what has actually been transacted on the exchange.

SPECULATION

Contrary to what many people believe, speculation is not gambling. Speculation is the skill of

analyzing data and taking positions on the various market situations to profits from favorable

price movements. In the stock market arena, this activity is also called trading.

OBJECTIVES OF THE STUDY

To study the suitable method of predicting price movement through technical analysis.

To evaluate previous frame to know entry and exit level of trading

To identify the buy signal and sell signal through chart movements with help of indicator

RESEARCH DESIGN

Analytical research design is adopted in this project. The main characteristic of this method is

that the researcher has no control over the variable. In this method the facts or information

are used which are already available, and analyze these to make a critical evolution of the

material.



The shares are chosen from the NSE India site, which are actively and highly traded

industries in the past one year.

No. Of Years : 1 year

No. Of Sectors : Bank

No. Of Companies : 5 companies

One year financial data collected from the bank sectors.

Year taken for study : 2010

SOURCES OF DATA:

The study is based on secondary data. The main sources of data are collected through

websites such as nseindia.com, bseindia.com, money control.com, Indiabulls.com and

Charting Software’s.

TOOLS USED FOR ANALYSIS

Moving average, Support and Resistance level

INTERPRETATION OF MARKET MOMENTUM

The following steps need before making any analyses of stocks. Because in technical

analysis we are concerned with identifying trend reversal at a relatively early stage and

assume that the new trend will continue riding that the new trend will continue riding that

trend until it reversal.

RESISTENCE AND SUPPORT LEVEL

Resistance

In simple words the meaning of resistance is opposition. As the name indicates, it opposes the

share price going in upper direction. It is the level where share price may stop before

continuing its upper journey.

But if the buying starts from all sides then no resistance come into picture the resistance level

is just broken and share price will continue its upward journey. To break the resistance level

volumes also play the major role.

If the share price moves above the resistance level with huge support of volumes then it is

considered as confirm up trend.

Once the resistance is broken then the share moves till its next resistance level or go in

consolidation (share movement with very less price variation) phase and then after getting

appropriate buying with good support of volumes then it tries to break its next resistance

level and will proceed and this continues.

The major bullish resistance is considered as 200 DMA (daily moving average) As long as

the share or index is trading above this level then it is considered as bullish or if share or

index moves from bottom and breaks this level then further upside is confirmed and on the

opposite side if the 200 DMA is broken from above then the down trend will continue and



this is what happened with Nifty and Sensex when they broke their 200 DMA in January

2008. Market has seen more than 60% fall after the broke of 200 DMA support level.

Resistance broken will act as support level (in case of moving average method)

SUPPORT LEVEL

As the name indicates it provides support for to share price to prevent it from falling further.

If the share price starts falling then it is expected that it may take halt at its support level but

if the selling and especially short selling is taking place then no support will comes into

pictures. If the selling pressure is from all sides then it may or may not take halt or wait near

its support level and will continue its downward journey till it finds next support levels.

MOVING AVERAGE

The market indices do not rise or fall in straight line. The upward and downward movements

are interrupted by counter moves. The underlying trend is studied by smoothing of the data.

To smooth the data moving average technique is used. The word moving means that the

body of the data moves ahead to include the recent observation. If it is six months moving

averages.

STOCK PRICES AND STOCK PRICES MOVING AVERAGE

Stock prices and stock prices moving average buy and sell signals are provided by the

moving averages. Moving averages are used along with the price of the scrip. The stock

price may intersect the moving average at a particular point. Downward penetration of the

rising average indices the possibility of a further falls. Upward penetration of a falling

average would indicate the possibility of the further rise and gives the buy signal



DATA ANALYSIS

6 MONTHS MOVING AVAREGE, JULY TO DECEMBER 2011

AXISBANK, ISIN: INE238A01026, Industry: Banks

CHART 1



STATE BANK OF INDIA

ISIN: INE062A08017, Industry: Banks

CHART 2

Rising Trend Buying Selling

Signal Signal

2000

2200

2400

2600

2800

3000

3200

3400

3600

6-Jul-10 6-Aug-10 6-Sep-10 6-Oct-10 6-Nov-10 6-Dec-10

closing price

avarage



ICICI BANK

ISIN: INE090A01013 | Industry: Banks

CHART 3

Flat trend line Falling trend line Rising trend line

FINDINGS

STOCK PRICE AND STOCK PRICES AVERAGE

The technical analysis studies the behavior of the price of the stock to determine the future

price of the stock. Stock price and stock price average is a tool for investors.

The moving average of the stock penetrates the stock market index from above; it generates

sell signals, and unfavorable market conditions that prevail for the particular scrip. Investors

have to concentrate on all information of shares. Not in moving average alone.

800

850

900

950

1000

1050

1100

1150

1200

1250

1300

6-Jul-10 6-Aug-10 6-Sep-10 6-Oct-10 6-Nov-10 6-Dec-10

Closing price

average price



BIBLIOGRAPHY

BOOKS

Technical analysis of stock trend - by Robert D. Edward & Magee

Martin Pring on market momentum - by Martin J. Pring

Technical analysis A to Z- by Steven B. Achilles

Business world magazines

Business line news paper

Security analysis and portfolio management - punithavathi pandiyan

WEBSITES

www.nseindia.com

www.bseindia.com

www.trendwatchindia.com

www.technicaltrends.com

www.chartschool.com

***


PRE AND POST ACQUISITION PERFORMANCE OF

PUBLIC AND PRIVATE SECTOR BANKS IN INDIA

Prof. Shanmugam venkatesan

Assistant Professor

Hindustan College of Arts & Science

India

Krishnan reddiyar Govindarajan

Professor, Department of Commerce

Annamalai University

Chidambaram, Tamil nadu

India

Abstract

In this paper we examine performance of public and private banks before and after

their activities acquiring other financial institutions. The merger and acquisitions activities of

the public sector and private sectors banks in India between 1995 and 2006 are considered for

the study. The performance of acquiring banks is undertaken based on ratio analysis. The

ratios pertaining to liquidity, activity, solvency and profitability are used to evaluate the

performance between two periods. Results of the empirical analysis shows that there is a

significant difference in the activity, solvency and profitability between pre and position

acquisition period for public sector banks. For private sectors banks, a strong difference in

liquidity status between two period are found. This study suggests that performance of public

and private sector banks is affected by their M & A activities.

Key Words: Merger and Acquisition (M & A), Interest spread and Parametric t-test


Introduction

Mergers and acquisitions (M&A) within the Indian financial sector have changed the

Indian banking landscape tremendously in the past two decades. The Indian banking sector

has witnessed significant structural changes that resulted in its consolidation through a large

number of mergers and acquisitions (M&As) and increased cross-shareholdings. Also, in

many countries, especially where smaller banks were active, the growth in M&As was

attributed to banks’ desire to increase in size in order to obtain gains in terms of market

power and/or efficiency.

While the bulk of the research on the financial performance of mergers and

acquisitions has focused on stock returns around the merger announcement, there are very

few research work in this area focusing on effect of M & As on firm performance by

comparing the various financial ratios between pre and post event period. In particular,

mergers have had a positive effect on key financial ratios of firms acquiring domestic firms

while a slightly negative impact on the firms acquiring cross-border firms. Therefore here an

attempt is made to evaluate the performance of acquiring banks based on comparing key

financial ratios before and after acquisition period of 5 years. The liquidity ratios, activity

ratio and profitability ratios during pre and post acquisition periods are compared. This study

analyses 11 mergers in the Indian banking sector between 1995 and 2006 to capture the effect

of M & A on firm performance.

Review of Literature

Measuring the performance of M&A deals has been a difficult problem for many

researchers. Scholars have used different techniques in the form of ratio analysis and

comparative analysis to identify the effects of M&A on acquiring companies. Rao and Sanker

(1997) found that there was a significant improvement in liquidity, leverage, and profitability

for acquiring firms. A majority of the acquiring firms were found to have some meaningful

synergies. In addition, the return on capital and return on total assets were increased

significantly. The risks, measured by variability in the earnings, of pre-merger firms were

found to be higher than that of post- merger firms (Kumar and Bansal, 2008). M&A activities

were also identified to improve the overall operational efficiency of acquirers at a significant

level. On the contrary, some studies revealed a mixed or negative impact of M&A deals on

acquirers’ performance. Selvam. M (2007), in his study on stock price reactions to mergers

and acquisitions activities taken place in banking industry with special reference to private

and public sector banks, has observed that M & A activities has affected profitability to some

extent and resulted in unhealthy competition among the players. Pawaskar (2001) found that

M&A did not result in improved performance or excess profit for the acquiring firms.

Instead, the only significant gains were through an increased leverage of the acquired firms.

In another study with ratio analyses, earning to equity ratio, liquidity ratio, and size ratio,

were founded to have positive effect on the for the targets, whereas pre-tax profit turned out

to be significantly negative (Renganathan, 1995).

Statement of the Problem

The Merger and Acquisitions have become one of the crucial strategic issues in the

banking industry in India nowadays. Although acquiring banks have frequently experienced

deteriorated post-acquisition performance that has reduced shareholders’ wealth, the M & A

is still one of the most common strategic instruments for expansion or restructuring. It is

known that acquisitions have a tremendous impact on the industry, but there is a definite lack

of comprehensive and systematic research about the underlying structure of the mergers and


acquisitions (M&A) phenomenon in the banking industry. Particularly there is a lack of

comprehensive research on financial performance combining M & A activities of banks

under public and private sector. So, the present research is undertaken to find out whether

expansion or restructuring of banks through M & A activities has improved the financial

performance or not.

Objectives of the Study

The present research work is carried out with objective of finding out the effect of M

& A activities on financial performance of all banks under public and private sectors by

comparing various ratios between pre and post-event period of five years.

Hypothesis

The following null hypotheses are framed for the present study:

(a) There is no significant difference in pre and post acquisition performance of Public

sector banks.

(b) There is no significant difference in pre and post acquisition performance of Private

sector banks

Methodology

Sample

A sample of bank merger announcements announced during the years between 1996

and 2006 are considered for the study (See Appendix). The merger announcements by banks

in both public and private sectors are taken into account.

Period of the Study

The M & A activities of banks under private and public sectors during the period from

1999 to 2004 are undertaken. However, for evaluating financial performance, the required

data for five years before and after M & A event are collected. Therefore, in respect of data,

the study period is 16 years from 1st April 1994 to 31

st March 2009.

Data

The present study is relied on secondary data, which are the financial statements for

five years before and after the M & A announcement years. The required data were gathered

from PROWESS data base.

Design

In order to evaluate the effect of Merger and acquisition activities of public and

private sector banks on their performance, ratio analysis method is adopted. The ratios

pertaining to liquidity (Current ratio, Quick ratio and Cash asset ratio), activity (Total income

to Net working capital, Total income to Total Assets ratio and Total income to Fixed asset

ratio), Solvency (Proprietary ratio and Credit / Deposit ratio) and profitability (Net profit

margin, Return on net worth and Return on capital employed) are calculated for pre and post

period of five years separately and ratios between two period are compared. A brief

explanation of above ratios are given below:

Current Ratio (CR)

The current ratio is the ratio used for testing the basic liquidity of a company. It

comprises of cash, accounts receivable, marketable securities, prepaid expenses, etc. It


signifies a company's ability to meet its short-term liabilities with its short-term assets. A

current ratio greater than or equal to one indicates that current assets should be able to satisfy

near-term obligations. A current ratio of less than one may mean the firm has liquidity issues.

Current Ratio = (Current Assets) / Current Liabilities

Quick Ratio (QR)

The quick ratio is a tougher test of liquidity than the current ratio. It eliminates certain

current assets such as prepaid expenses that may be more difficult to convert to cash. Like the

current ratio, having a quick ratio above one means a company should have little problem

with liquidity. The higher the ratio, the more liquid it is, and the better able the company will

be to ride out any downturn in its business.

Quick Ratio = (Cash + Accounts Receivable + Short-Term or Marketable

Securities) / (Current Liabilities)

Cash Asset Ratio (CSHRAT)

This ratio indicates a conservative view of liquidity such as when a company has

pledged its receivables and its inventory, or the analyst suspects severe liquidity problems

with inventory and receivables. It is calculated as follows:

Cash Asset Ratio = Cash Equivalents + Marketable Securities / Current

Liabilities

Total Income to Working Capital Ratio (TIWC)

Indicates efficient use of working capital in generating income. A low ratio indicates

inefficiency, while a high level implies that the company's working capital is working too

hard.

TIWC = Total Income / Working capital

Total Income to Total Asset Ratio (TITOAST)

Measures the activity of the assets and the ability of the business to generate income

through the use of the assets.

TITOAST = Total Income / Total Assets

Total Income to Net Fixed Asset Ratio (TITONFA)

Measures the capacity utilization and the quality of fixed assets. It is calculated as

follows:

TITONFA = Total income / Net Fixed Assets

Interest Expended to Interest Earned Ratio (INTEXPEARN)

Indicates the relationship between interest expended on deposits and interest earned

on lending. This ratio is also called interest spread ratio. The formula for this ratio is:

INTEXPEARN = Interest Expended / Interest Earned

Proprietary Ratio

This ratio exposes the relationship between shareholders’ capital and total assets. The

shareholders’ capital consist of equity paid up and reserves less accumulated loss. This ratio

is used by the investors to know how safety a bank against losses and insolvency.

Proprietary Ratio = Shareholders’ Capital / Total Assets * 100


Credit Deposit Ratio

This ratio is used to assess short-term solvency position of a bank. The ratio is nothing

but proportion of advances to deposits. Advances includes loans, cash credit, overdrafts and

bills discounted. This ratio indicates how effectively the deposits of the bank have been

utilized for generating revenue.

Credit Deposits Ratio = Advances / Deposits

Net Profit Margin (NPM)

The profit margin tells you how much profit a company makes for every one rupee 1

it generates in revenue or sales. Profit margins vary by company (firm or industry), but all

else being equal, the higher a company's profit margin compared to its competitors, the better.

It is calculated as:

NPM = Net Profit After Tax / Total Income

Return on Net Worth (RONW)

This ratio is used to analyze the ability of the firm’s management to realize an

adequate return on the capital invested by the owners of the firm. Tendency is to look

increasingly to this ratio as a final criterion of profitability. The formula is:

RONW = Net Profit After Taxes / Net Worth (Shareholders’ Equity)

Return on Capital Employed (ROCE)

Return on capital employed (ROCE) is the rate of return a business is making on the

total capital employed in the business. Capital will include all sources of funding

(shareholders funds + debt). To be consistent with this the return should be taken prior to

interest (the return to lenders) and tax. It is therefore

ROCE = PBIT / (Total Assets – Current Liabilities)

Statistical Tool

The statistical significance of the difference in ratios between pre and post event

period of five years are tested using parametric t-test.

Results and Discussion

It can be seen from Table I that the liquidity position of the public sector banks in

terms of CR, QR and Cash Ratio tend to experience with trivial decline against their deals

associated with acquisition of other banks. The scenario is reverse in the case of turning

working capital into earnings That is, efficient use of working capital do not differ between

periods.

Regarding their activities, in turning their total assets and fixed assets into generating

income, there has been remarkable decline after acquisition activities. That is, the TITOAST,

on an average for five years, 0.0977 times in pre-period has declined to 0.0808 times in post-

period and the difference in these two values is significant at 1 per cent level (t value = 6.58,

p < 0.01). Similarly, the TITONFA on an average for 5 years has significantly declined to

11.8737 times during post-period from 14.2371 times in pre-period (t-value = 1.71, p < 0.10).

At the same time interested expended to interest earned, which is 0.7781 times in pre-period

has declined significantly to 0.6874 times in pre-period (t-value = 2.04, p < 0.05). A

significant increase of proprietary ratio of 0.0489 times in pre-period to 0.0599 times in post-

period (t-value = -3.74, p < 0.01), it is apparent that there has been a remarkable increase in


owners’ equity relative to total assets after acquisition activities of public sector banks.

Similarly, there has also been a notable increase in extending credit to the customers relative

to mobilization of deposits from 0.5189 times in pre-period to 0.5723 times in post-period (t-

value = -2.80, p < 0.01).

As far as the profitability is concerned, RONW and ROCE, on an average for five

years before and after acquisition event remain same. That is, there is no remarkable

difference in these two profitability ratios between two period. However, Net earnings (Net

profitability margin) on the average for five years, which stood at 5.83 per cent in pre-period,

has increased significantly to 8.73 per cent in post-period (t-value = -3.82, p < 0.01). On the

whole, it is concluded that the M & A activities of public sector banks have significant

negative effect on utilization of assets in generating income but there has been a positive and

significant influence on interest spread (interested expended relative to interest earned),

owners’ capital and advances to deposits (solvency) as well as on making profit net of all

expenses.

The financial performance of private sector banks before and after their acquisition

activities are evaluated by comparing various ratios pertaining to liquidity, activity and

profitability between pre and post period 5 years and the results of the analysis are presented

in Table II. It can be observed from the table that the performance of private banks during

five years after acquiring other banks is not attractive. The liquidity position become weak

during post-event period of 5 years. The CR, QR and CSHRAT, which is 4.3040 times,

4.2690 times and 3.2822 times on an average in pre-event period of five years has declined

significantly to 1.3430 times (t-value = 4.29, p < 0.01), 1.2050 times (t value = 4.43, p <

0.01) and 0.9293 times (t-value = 4.12, p < 0.01) on an average during post-event period of

five years respectively.

At the same time, efficiency in utilization of working capital for generating income is

unaffected by the acquisition activities. That is, decline in TIWC from 1.1448 times in pre-

period to 1.0834 times in post-period is trivial. However, efficiency of the private sector

banks in generating income relative to assets has come down significantly from 0.0931 times

in pre-period to 0.0700 times in post-period (t value = 2.09, p < 0.05). It can be seen that ratio

of interest expended to interest earned is 0.7697 times in pre-period has declined to 0.6828

times in post-period, but there is no significant difference in mean ratios. That is there is no

notable change in interest spread due to acquisition activities of private sector banks. At the

same time, owners’ fund in total investments has come down from 0.1780 times in pre-period

to 0.0731 times in post-period. On the other hand, lending credit to the customer against

mobilization of deposits has increased significantly from 0.4638 times to 0.7889 times

between pre and post acquisition periods (t-value = -2.63, p < 0.01).

As far as the effect of acquisition activities on profitability of the private sector banks

is concerned, no notable change in NPM as well as in RONW (t-value is insignificant)

between pre and post period of five years is found. However, the profitability, on an average

for 5 years, relative to capital employed has declined at marginal level from 11.5430 per cent

in pre-period to 7.5140 per cent in post period (t-value = 1.84, p < 0.10). Hence, from the

results comparing the liquidity, activity, solvency and profitability ratios, between pre and

post-acquisition period of five years, it is found that the deals acquiring other limited banks

by private sector banks have significant negative effect on their liquidity position as well as

on their overall financial performance.

Conclusion

Out empirical analysis of financial performance against acquisition activities of public

and private sector banks has led to the finding that the performance of private sector banks is


found to be better in pre-period compared to their performance in post-acquisition period. It

is further found that there is notable change in liquidity position of the public sector banks

due to their acquisition activities whereas there has been significant decline in their activities

in turning their assets for generating income. It is however found that the net earnings of

public sector banks has increased significantly after acquiring other banks likely due to a

notable decline in interest expended relative to interest earned. Overall, the performance of

public sector banks in terms of generating income relative to their investment in fixed assets

is significantly and negatively affected whereas their performance in respect of their net

earnings is positively influenced by acquisition deals due to increase in interest spread. The

deals pertaining to acquiring other (private limited) banks by private sector banks have

significant negative effect on their liquidity position as well as on their overall financial

performance. Hence, both hypotheses are rejected and alternatively it is concluded that there

is impact of M & A on financial performance of both Public and Private sector banks in

India.

Table I

Comparison of Various Ratios between Pre and Post Acquisition Period of 5 Years for

PUBLIC Sector Banks

Financial Ratios Pre Period Post Period t-value

Mean

(SD)

Mean

(SD)

Current Ratio (CR) 4.3106 3.8920 0.81

(2.1958) (2.1057)

Quick Ratio (QR) 4.0520 3.6746 0.77

(2.1019) (1.9829)

Cash Ratio (CSHRAT) 3.1506 2.9334 0.57

(1.6893) (1.4826)

Total Income to Net Working Capital

(TIWC)

0.8686 0.9192 -0.47

(0.4890) (0.4084)

Total Income to Asset Turnover Ratio

(ASTTO)

0.0977 0.0808 6.58***

(0.0077) (0.0131)

Total Income to Fixed Asset Turnover Ratio

(FATO)

14.2371 11.8737 1.71*

(6.9422) (4.3268)

Interest Expended to Interest Earned 0.7781 0.6874 2.04**

(0.1882) (0.1838)

Proprietary Ratio 0.0489 0.0599 -3.74***

(0.0150) (0.0088)

Credit Deposit Ratio 0.5189 0.5723 -2.80***

(0.0640) (0.0929)

Net Profit Margin (NPM) 0.0583 0.0873 -3.82***

(0.0340) (0.0293)

Return on Net Worth (RONW) (%) 14.6846 15.2780 -0.51

(4.7653) (4.9911)

Return on Capital Employed (ROCE) (%) 9.7034 10.4354 -0.68

(4.6332) (4.3074)

Figures in brackets are standard deviation

***Significant at 1% level; **Significant at 5% level; *Significant at 10% level


Table II

Comparison of Various Ratios between Pre and Post Acquisition Period of 5 Years for

PRIVATE Sector Banks

Financial Ratios

Pre Period Post Period

t-value Mean

(SD)

Mean

(SD)

Current Ratio (CR) 4.3040 1.3430 4.29***

(2.1378) (0.4496)

Quick Ratio (QR) 4.2690 1.2050 4.43***

(2.1491) (0.3992)

Cash Ratio (CSHRAT) 3.2822 0.9293 4.12***

(1.7695) (0.3569)

Total Income to Net Working Capital

(TIWC)

1.1448 1.0834 0.09

(1.6130) (1.4728)

Total Income to Asset Turnover Ratio

(ASTTO)

0.0931 0.0700 2.09**

(0.0267) (0.0227)

Total Income to Fixed Asset Turnover Ratio

(FATO)

2.9560 3.9700 -1.64

(1.1944) (1.5405)

Interest Expended to Interest Earned 0.7697 0.6528 1.31

(0.2537) (0.1240)

Proprietary Ratio 0.1780 0.0731 1.51

(0.2188) (0.0109)

Credit Deposit Ratio 0.4638 0.7889 -2.63**

(0.1926) (0.3393)

Net Profit Margin (NPM) 0.1295 0.1296 -0.004

(0.0636) (0.0287)

Return on Net Worth (RONW) (%) 16.5110 16.0950 0.11

(9.2116) (7.5001)

Return on Capital Employed (ROCE) (%) 11.5430 7.5140 1.84*

(4.1188) (5.5644)

Figures in brackets are standard deviation

***Significant at 1% level; **Significant at 5% level; *Significant at 10% level


References

Healy, P.M., Palepu, K.G., and Ruback, R.S. (1992) Do Mergers Improve Corporate

Performance?, Journal of Financial Economics, 31(2), pp. 135-175

Mishra, P. (2005) Mergers and Acquisitions in the Indian Corporate Sector in the Post-

Liberalization Era: An Analysis, Ph.D Dissertation, (West Bengal: Vidyasagar University)

Dickerson, A. P., Gibson, H. D., and Tsakalotos, E. (1997), "The Impact of Acquisitions

onCompany Performance: Evidence from a Large Panel of UK Firms,” Oxford Economic

Papers, 49(3), pp. 344-61.

Selvam, M. 2007. Mergers and Acquisitions in the Banking Sector- The Indian Scenario.

S.Viswanathan (Printers & Publishers) Pvt. Ltd.

Pawaskar, V. (2001) Effect of Mergers on Corporate Performance in India, Vikalpa, 26(1),

pp.19-32

Rao K V and Sanker K R (1997), “Takeover as a Strategy of Turnaround”, UTI Edited book,

pp. 47-56

Renganathan V S (1995), “Takeover of industrial firms in india: an empirical analysis”,

Prajanan, Vol. 24, No. 2, pp.103-110.

Satish Kumar, Lalit K. Bansal, (2008) "The impact of mergers and acquisitions on corporate

performance in India", Management Decision, Vol. 46 Iss: 10, pp.1531 – 1543

Appendix

Particulars of Bank Mergers Between 1996 and 2006

Acquiring Banks Target Banks Event Date

PUBLIC SECTOR BANKS

Bank of Baroda Barelly Corporation Banks Ltd 03.06.1999

Bank Of Baroda Banaras State Bank Ltd 20.07.2002

Bank Of Baroda South Gujarat Local Area Bank Ltd 25.06.2004

Oriental Bank Of Commerce Punjab Co.op Bank and

Bari Doab Bank Ltd 08.04.1997

Oriental Bank Of Commerce Global Trust Bank Ltd 14.08.2004

Punjab National Bank Nedungadi Bank Ltd 01.02.2003

State Bank Of India Kashinath Seth Bank 01.01.1996

PRIVATE SECTOR BANKS

H D F C Bank Ltd. Times Bank Ltd 26.02.2000

I C I C I Bank Ltd. Bank of Madura 10.03.2001

***

research journal of commerce & behavioural science - rjcbs

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