ijrime complimentary copy vol1 issue5

IJRIME Volume1Issue5 ISSN-2249- 1619

International Journal of Research in IT, Management and Engineering www.gjmr.org

Sr.

No.

TITLE & NAME OF THE AUTHOR(S) Page

No.

1 REAL TIME NETWORK MONITORING SYSTEM IN LAN ENVIRONMENT

M. Shoaib Yousaf , Ahmed Mattin , Ahsan Raza Sattar

1

2 QUALITY OF WORKING LIFE IN INSURANCE SECTOR

Rita Goyal

12

3 REFACTORABILITY ANALYSIS USING LINEAR REGRESSION

Gauri Khurana, Sonika Jindal

23

4 OPTIMIZING FILTERING PHASE FOR NEAR‐DUPLICATE DETECTION OF WEB PAGES USING TDW‐MATRIX

Tanvi Gupta

38

5 STUDY AND DESIGN OF BUILDING INTEGRATED PHOTO VOLTAIC SYSTEM AT HCTM CAMPUS KAITHAL, HARYANA

Rajeev Kumar, Gagan Deep Singh

47

6 FUNDS MANAGEMENT OF ICICI BANK

Manju Sharma

64

7 EMERGING TRENDS IN HUMAN RESOURCE MANAGEMENT—A CHALLENGE TO THE ITES

Raunak Narayan

77

8 FUNDAMENTAL CHALLENGES IN EMERGENT FIELD OF SENSOR NETWORK SECURITY AND INITIAL APPROACHES TO SOLVE

THEM

D. P. Mishra, M. K. Kowar

88

9 THE ECONOMICS & BUSINESS OF EUROPEAN LEAGUE FOOTBALL

Rosy Kalra

105

10 AN ALGORITHM FOR SOLVING A CAPACITATED FIXED CHARGE BI‐CRITERION INDEFINITE QUADRATIC TRANSPORTATION

PROBLEM WITH RESTRICTED FLOW

S.R. Arora, Kavita Gupta

123

11 IMPACTS OF USE OF RFBIDW ON TAXATION

Sulatan Singh, Surendra Kundu, Madhu Arora

141

12 EVALUATION OF KNOWLEDGE MANAGEMENT LEVEL OF EDUCATIONAL INSTITUTIONS USING FCE AND AHP

Mohit Maheshwarkar, N. Sohani, Pallavi Maheshwarkar

148

13 EVALUATION OF KNOWLEDGE MANAGEMENT LEVEL OF EDUCATIONAL INSTITUTIONS USING ANALYTICAL HIERARCHY

PROCESS: A CASE STUDY IN INDIA

Mohit Maheshwarkar, N. Sohani, Pallvai Maheshwarkar

165

14 PROBE FEED RECTANGULAR PATCH MICROSTRIP ANTENNA: CAD METHODOLOGY

R.D. Kanphade, D.G. Wakade, N.T. Markad

180

15 DETERMINANTS OF GROWTH OF TOURISM INDUSTRY IN GOA: A STUDY

Dr. Achut Pednekar

191

IJRIME Volume1Issue5 ISSN‐2249‐ 1619

International Journal of Research in IT, Management and Engineering www.gjmr.org 1

REAL TIME NETWORK MONITORING SYSTEM IN LAN

ENVIRONMENT

M. Shoaib Yousaf *

Ahmed Mattin *

Ahsan Raza Sattar*

ABSTRACT

In this research thesis, I have compared different NMS tools and their feature. I have also

analyzed the available three SNMP versions and compare them in respect of security to select

which one is best to use. The SNMP v1 and v2 have most of similar features but in SNMPv2

some modifications were made to overcome the deficiencies in version 1. After that SNMP

version 3 (SNMPv3) added security and remotely configurations is added in the earlier versions

and SNMP v3 is now most up to date version available today. I have examines the two methods

to secure network traffic i.e. SNMP v3, the latest version and combination of SNMP with the

non secure version like Internet Protocol Security i.e. SNMP over IPSec. These two techniques

implement authorization, safety and privacy of network traffic passing through SNMP.

Keywords: NMS, LAN, SNMP, TCP /IP, IPSec.

*Computer Science Department, University of Agriculture, Faisalabad, Pakistan



INTRODUCTION

Network management systems are use to make sure accessibility and complete take care of

computers and network devices installed in LAN. An NMS is able of detection and report

failures of devices configured in network to administrator efficiently. NMS continuously send

messages across the network to all other host to confirm their status. When failures of devices

and slow responses from devices shown, then these systems send extra messages called alerts to

inform system administrators regarding the problems.

To have control of overall network, administrator wants to know the condition of all devices on

configured on the network i.e. Data flowing in / out from each host etc. there is a protocol

available within the TCP / IP suite called Simple Network Management Protocol (SNMP) to

meet this purpose (Amir and Maccane, 2003).

Administrator used multiple tools for monitoring the internet as there is no restriction to select

specific monitoring tool available. E.g. to have complete view of network devices on the internet,

shared intranet, mail servers, database servers etc administrators use IP monitor software and

update them upon receiving alerts via alarms, messages or e-mail etc is case of a connection fails

(Bradley, 2002).

The basic idea of this thesis is to compare the different NMS tools and their feature. In this

research paper we will discuss the available three SNMP versions. The SNMP v1 and v2 have

most of similar features but in SNMPv2 some modifications were made to overcome the

deficiencies in version 1. After that SNMP version 3 (SNMPv3) added security and remotely

configurations is added in the earlier versions and SNMP v3 is now most up to date version

available today. Our main target is to examines the two methods to secure network traffic (i)

SNMP v3, the latest version (ii) combination of SNMP with the non secure version like Internet

Protocol Security i.e. SNMP over IPSec. These two techniques implement authorization, safety

and privacy of network traffic passing through SNMP.

MATERIALS & METHODS

In this section the main focus is on the design of the network management system as well as the

major parts of the system will be discus in this chapter. Also different parts and how these parts



correlate each other in network management system to work will be discuss here. We are going

to compare the SNMP versions available and find out the better one to be used with network

management system. Also administrator should be well aware of the security issues such as

ability to restore, capable to delete / add user, able to monitor network accessibility, amount of

traffic, rerouting, user authentication and response time of the faults.

WORKING MECHANISM

SNMP was proposed as a protocol that manages the nodes of network such as important servers,

workstations, routers, switches etc. SNMP protocol is placed inside the UDP transport layer

which is a connectionless layer in OSI model. To calculate the network performance, to locate

the hosts and resolve network problem and to update the network, SNMP is used. SNMP

managed networks consists of there fundamental parts: NMS devices, NMS agents and NMSs.

An SNMP managed device comprises of an SNMP agent which is placed inside the network and

watches all activities of network. The SNMP agent collects all the network information and

stores that information to the use of this information by NMSs. All devices of network like

routers, servers, switches and printers etc are control by the NMSs in the network. An agent is

placed inside the SNMP device that is regularly watching all events of network. SNMP agent is

provided limited access to the collected data and converted this data to a readable form necessary

to use with SNMP.

How NMS Works (Swee, 2006).

Three versions of SNMP are most commonly used: SNMP v1, SNMP v2 and SNMP v3. The

both versions 1 and 2 are similar in function except that in v2 security has been enhanced to



overcome the security issues. Keeping in view the importance of security a new version SNMP

v3 was developed that covers all the security issues and provide more features like remote

configuration.

SNMP v1 is placed inside the layers of OSI and performs its functions independently without

any disturbance to those OSI layers. SNMPv1 is most commonly used protocols in early days

and before the invention of next version. An NMS generates a request to devices and devices

respond back to these requests. There are four operations used in v1: Get, Get Next, Set, and

Trap. The Get command used to request objects their values by the NMS. The Get Next

operation is used to request the next value in the table. The Set operation used to fix the values

inside SNMP agent. The last operation that is used for updating any change of the network to

NMS is Trap. The basic limitations in version 1 are the security i.e. message authentication and

protection from outside intruders. SNMP v2 was designed in 1993 to overcome above problems

and was to be an improvement of its ancestor.

SNMPv2 was modified then with GetBulk and Inform operation after version 1. The GetBulk

function collects the huge block of information simultaneously and provides access to NMS to

this information. And Inform function is used in communication of one NMS with another NMS

using trap operation and then receives a response from other NMS. The major area enhanced in

SNMP v2 was security that makes developers for its invention. SNMP v2 has different message

formats. The difference in version 1 and 2 is purely in the field of security. However message

format is same as of version 1 in the UDP for version 2. More security and remote configuration

is added in newer version SNMP V3 that protects messages and provide an easy module to

access these messages for SNMP.

A new characteristic that was not available in previous versions is the user friendly view module

for SNMPv3 addition. This feature allows the elements to control the access to the important

information. SNMP engine having VACM that is consists of many message formats with

different security models. This improvement in NMS and SNMP is suitable for all types of

hardware. In SNMPv3 security is modified into three levels: upper level is authentication and

privacy, middle level is authentication with no privacy and the bottom level is no authentication



no privacy. SNMP has the ability to reboot the network devices due to its security features.

Below figure 3.4.3 shows security subsystem of SNMP v3 (Swee, 2006).

COMPARATIVE STUDY OF EXISTING SYSTEMS

It is a basic requirement that the network which I selected must have the capability to reduce the

problems and other issues of traffic concerning with the delay, response time and throughput.

Several materials are existing on the internet or market as concern to these networks and their

relevant problems, furthermore several procedure also exist concerning to the each kind of

networks. But the research is concerned with the performance analysis of NMS protocols and

selecting best one protocol from them. Certain issues are there regarding to the types of traffic,

throughput, latency and network availability. These issues are very common and challenging for

the administration especially in those organizations having WAN link contains the routing

devices. Such organizations can suffer from various kinds of issues regarding to the traffic delays

if the careful selection of the proper network is not made by suspicious investigation.

RESULTS

I have analyzed security of SNMP in this research thesis to conclude which is best to be used in

network. I have examined two techniques of security for secure SNMP traffic: firstly SNMPv3,

most up-to-date invention of SNMP and non secure version of SNMP in a combination of

Internet Protocol Security (IPSec). The security used in SNMP V2 consumes less network

capacity as compare to SNMPv3 and also provides security to IP application which is not

possible in SNMP v3. Also reduces load on administrators in configuring, managing, and

maintaining monitoring systems so that their concentration is focused more on higher level

policies and critical abnormal circumstances also discusses in previous chapter.

Result 1 for one variable

The network capacity used by SNMP is examine by running the SNMP agent with the help of an

SNMP management function. The IPSec used a tunnel mode security mechanism to

communicate between the gateways. Ethereal captured the IP packets generated by SNMP

operations running of the host machine are shown in below table 3.3.1.



SNMP Version /

Security Scheme

Get Response Total

V2c 78 102 180

V2c over IPSec 137 153 288

V3 noAuthNoPriv 141 165 306

V3 authNoPriv 153 177 330

V3 authPriv 168 192 358

V3 noAuthNoPriv over

IPSec

191 217 408

V3 authNoPriv over

IPSec

209 233 440

V3 authPriv over IPSec 223 249 472

Table 1 shows the SNMP-Get messages, SNMP-Response messages and the total of SNMP

Get/Response sizes in byte using different security schemes for one variable.

Result 2 for seven variables

The second result is almost same as we get the first except it is obtain using 7 variables.

SNMP Version / Security

Scheme

Get Response Total

V2c 176 288 464

V2c over IPSec 233 345 578

V3 noAuthNoPriv 249 351 590

V3 authNoPriv 251 363 614

V3 authPriv 265 378 643

V3 noAuthNoPriv over IPSec 289 401 690



V3 authNoPriv over IPSec 305 417 722

V3 authPriv over IPSec 321 433 754

Table 2 shows the SNMP-Get messages, SNMP-Response messages and the total of SNMP

Get/Response sizes in byte using different security schemes for seven variables.

From the above results we can conclude that the IPSec using authentication and triple-DES

encryption scheme consume 57 bytes more than the normal IP packet moving this payload. Also

SNMPv3 consume 89 bytes more than the normal IP packet by using HMAC-MD5- 96

authentication and DES encryption schemes.

RESULT 3 NETWORK CAPACITY CONSUMED BY SNMP

The SNMP agent running on gateways is used to get the processing time consumed by a secure

SNMP operation. Ethereal captured the IP packets generated by the SNMP-Get operation

running on observer host. We use node to node tunnel-mode security connection to distinguish

the source of packet and destination of packet. As DES encryption scheme processing is

computationally extremely intensive and by using triple-DES adds three times more processing

than DES. But we can experiment to draw results to gain insight conclusions. The Processing

time interval can be define as the time from capturing the SNMP Get message by Ethereal to the

time corresponding the SNMP Response Message. Table 3.3 shows the average processing time

interval and the standard deviation calculated for both approach.

SNMP Version / Security Scheme Mean Time

Standard Deviation

V2c 310.4 12.2

V3 noAuthNoPriv 525.9 6.5

V3 AuthNoPriv 591.7 6.1

V3 AuthPriv 696.8 57.7

V2c over IPSerc 778.8 80.1

V3 noAuthNoPriv over IPSec 1057.0 19.4



V3 AuthNoPriv over IPSec 1160.0 21.2

V3 AuthPriv over IPSec 1457.7 79.5

Table 3 shows the network capacity consumed by SNMP.

RESULT 4 CAPACITY CONSUMED BY SNMP V3 FOR DISCOVERING EXCHANGE

We calculate the capacity consumed by SNMPv3 during discovering exchange for SNMP-Get

message, its corresponding SNMP-Report message and the total bytes used in discovery

exchange. From the result shown below we can predict that a SNMPv3 discovery exchange is

same in size and function to a typical SNMP Get/Response exchange. A more stylish SNMP

management suite remembers the most recent timeliness parameters received from each

SNMPv3 unit to which it communicates, thus reducing the need for discovery exchanges.

SNMP Version Request Report Total

SNMP V3 AuthPriv 102 139 241

SNMP V3 AuthPriv

over IPSec

159 193 352

Table 4 shows capacity consumed by SNMP v3 for discovering exchange.

RESULT 5 CAPACITY CONSUMED BY AN IPSEC

To get the result of network capacity consumed by IPSec Free S/WAN IPSec tool is configured

to keep informed about security between the gateways every minute. Many of these updates are

also capture by the ethereal application running on host observer. Below table shows the IP

packet sizes (in bytes) for all nine packets captured while the initial tunnel-mode security

association is established.

Packet # Mode Length

1 Main 204

2 Main 108



3 Main 208

4 Main 208

5 Main 96

6 Main 96

7 Quick 344

8 Quick 320

9 Quick 80

Table 5 shows network capacity consumed by IPSec.

SUMMARY / CONCLUSION

From the obtained results in previous chapter, we conclude that the version 3 of SNMP required

24 % more capacity of network than the use of SNMP v2 with IPSec design. Also with the

change in the size of application layer, the output of SNMP v2 with IPSec changes significantly.

Both techniques SNMPv2 over IPSec and SNMPv3 overheads network devices equally. It will

doubles the processing overhead of devices in SNMP v2 when used authentication and

encryption schemes and when installing IPSec on that device. We can get better results if we

used security and SNMP processing on separate devices. The security gateway is different from

network devices where SNMP agent is implemented in case of SNMP v2 over IPSec. However

in SNMP v3 both security processing and SNMP processing are running on single devices which

creates problems to implement SNMP v3.

The discovery exchange with SNMP v3 consumes 240 more bytes of network capacity. The

complexity of SNMP application effect on discovery exchanges frequency. There is no As

SNMP application has no feature to store the parameters of timelines, hence efficiency of

network capacity badly affected in discovering process making network more overloaded.

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QUALITY OF WORKING LIFE IN INSURANCE SECTOR

Rita Goyal*

ABSTRACT

The study of Quality of working life has been an important and critical area in management and

organizational performance from last several years especially in the LIC.. This paper aims to

study the extent of QWL in the LIC, and explores the proposed link between the QWL and

employees productivity. Two hundred fifty employees responded to the researcher’s

questionnaire. The study makes use of statistical techniques such as mean, standard deviation, t

test. ANOVA analysis to process and analysis the data collected for this study .The demographic

portion of the instrument was developed by the researcher to sort out the demographic

information. To explore difference between the means of two group t-test was applied. One way

ANOVA was used for exploring the difference among more than two groups. The paper ends by

offering useful suggestions to the management involved in the operations of the corporations.

Key words: Quality of working life, Insurance Sector, Competency Development, Employees

Productivity, Work-Life Balance

*Lecturer Dept. of Humanities and Social Sciences, Maharishi Markendeshwar University,

Mullana (Ambala)



INTRODUCTION

Quality of Working Life is a process of work organizations which enables its members at all

levels to actively participate in shaping the organization environment, methods and outcomes.

Conceptual categories which together make up the quality of working life are adequate and fair

compensation, safe and healthy working conditions, immediate opportunity to use and develop

human capacities, opportunity for continued growth and security, social integration in the work

organization, constitutionalization in the work organization, work and the total life space and the

social relevance of work life. Quality of Work Life was the term actually introduced in the late

1960’s. From that period till now the term is gaining more and more importance everywhere, at

every work place. Initially quality of work life was focusing on the effects of employment on the

general well being and the health of the workers. But now its focus has been changed. Every

organization need to give good environment to their workers including all financial and non

financial incentives so that they can retain their employees for the longer period and for the

achievement of the organization goals. The concept of QWL is based on the assumption that a

job is more than just a job. It is the center of a person’s life. In recent years there has been

increasing concern for QWL due to several factors: Increase in education level and consequently

job aspirations of employees; Association of workers; Significance of human resource

management; widespread industrial unrest; Growing of knowledge in human behaviors, etc.

LITERATURE REVIEWS

Bear field, (2003) used 16 questions to examine quality of working life, and distinguished

between causes of dissatisfaction in professionals, intermediate clerical, sales and service

workers, indicating that different concerns might have to be addressed for different groups. The

distinction made between job satisfaction and dissatisfaction in quality of working life reflects

the influence of job satisfaction theories. Lawler, (2004) Quality of Working Life is not a

unitary concept, but has been seen as incorporating a hierarchy of perspectives that not only

include work-based factors such as job satisfaction, satisfaction with pay and relationships with

work colleagues, but also factors that broadly reflect life satisfaction and general feelings of

well-being suggested that quality of working life was associated with satisfaction with wages,

hours and working conditions, describing the “basic elements of a good quality of work life” as:



safe work environment,

equitable wages,

Equal employment opportunities and opportunities for advancement.

Waddell Jane and Carr Paul (2005) In addition to competition of globalization and products,

organization face competition related to employee retention at the same time employees face

competition for their time. As increasing number of employees face competing demands between

work and family, the importance of maintaining a healthy work life balance is of paramount

consideration. In spite of family- friendly policies, many employees perceive negative

consequences associated with availing themselves of these policies. At the same time, over 50%

of American employees fail to take their allotted vacation time. Failure to achieve a healthy work

life balance can lead to overload, which may result in loss of employees. Encouraging a healthy

work life balance benefits both the organization and the employees. Lawler and Porter (2006).

An individual’s experience of satisfaction or dissatisfaction can be substantially rooted in their

perception, rather than simply reflecting their “real world”. Further, an individual’s perception

can be affected by relative comparison – am I paid as much as that person - and comparisons of

internalized ideals, aspirations, and expectations, for example, with the individual’s current state

In summary, where it has been considered, authors differ in their views on the core constituents

of Quality of Working Life (e.g. Sirgy, Efraty, Siegel & Lee, 2001 and Warr, Cook & Wall,

1979). It has generally been agreed however that Quality of Working Life is conceptually similar

to well-being of employees but differs from job satisfaction which solely represents the

workplace domain. Banerjee Indranil (2006) Jobs are getting increasingly demanding, as the

organization face competition and become leaner in structure, leading to conflict between

people’s professionals deliverable and personal requirements. It is acknowledged that continuous

disregard of personal issues ultimately lead to employees’ underperformance and so people often

discuss work life balance but seldom act on it. So, the focus now is “Who is going to bell the

cat?” For tackling the problem, multi-pronged effort, comprising the organization, the employee,

the Government, the Industry, the society, etc., is required. Tekuru Siva ram (2007) Work- life

balance is all about need for individuals having complete control over their work, i.e. deciding

when, why, where and how to work. Finding these pressures encroaching into their private life

and time, they are unable to do anything about it and are finally squeezed out. Organization

should consider Work –life balance as an extension of the fringe benefits offered to the



employees. This will help both the employees and the organization. Aggarwala Tanuja (2007)

Conflicting demands and pressures from works and life (family) can interfere with each other

since the two domains are complementary, not conflicting priorities. Acceptance of this reality

by the organization and new business and societal trends, have seen the growth of family-

friendly practices at work place. Adopting a win- win approach, growing number of organization

believe that helping employees balance and integrate their work lives with the rest of their lives

leads to positive outcomes for both the employee and the employer. Work- family practices

should be viewed as a part of overall HR and business strategy that is related to a firm’s

competitive advantage. Swamy (2007) In today’s business context the pressures of work have

been intensifying and there is a growing feeling among employees that the demand of work

being to dominate life and a sense of work-life imbalance is felt. The challenge of integrating

work and family life is a part of everyday reality for the majority of employees. Organizations

have to continually innovate and come up with programs that provide scope for employees to

balance their responsibility at their work place and interest they have outside work.

Suman Ghalawat (2010) states that QWL is a Process of work organizations which enables its

members at all levels to actively participate in shaping the organizations’ environment, methods

and outcomes. This value based process is aimed towards meeting the twin goals of enhanced

effectiveness of organization and improved quality of the life at work for employees. Work is an

integral part of our everyday life, as it is our livelihood or career or business. On an average we

spend around twelve hours daily in the work place, that is one third of our entire life; it does

influence the overall quality of our life. It should yield job satisfaction, give peace of mind, a

fulfillment of having done a task, as it is expected, without any flaw and having spent the time

fruitfully, constructively and purposefully. Even if it is a small step towards our lifetime goal, at

the end of the day it gives satisfaction and eagerness to look forward to the next day. The factors

that influence and decide the Quality of Work Life are: Attitude, environment, opportunities,

nature of job, people, stress level, career prospects, growth and development, risk involved and

reward.

OBJECTIVES OF STUDY

In light of the domain for research, the study was undertaken:-



1. To examine the nature of quality of working life prevailing in some selected Branches of LIC.

2. To study the differences in the perception of employees on the basis of gender.

3. To study the differences in the perception of employees on the basis of designation.

4. To study the differences in the perception of employees on the basis of Qualification.

HYPOTHESIS

In view of the objectives set for the study, following null hypothesis was formulated:

Ho1.1 There is no significant difference between the perception of male and female employees

regarding quality of working life.

Ho1.2There is no significant difference between the perceptions of employees at different levels

regarding quality of working life

Ho1.3 There is no significant difference between the perception of graduate and post graduate

employees regarding quality of working life.

RESEARCH METHODOLOGY

Data

A total of 400 employees were chosen randomly from the 4branches, keeping in view their total

strength and range of activities. Out of 400 questionnaires distributed only 250questionnaires

were received completed in all respects. Therefore with 62.5% response rate the researcher has

conducted this study.

SAMPLE OF THE STUDY

Following table represents the sample of study:

Gender-wise distribution of employees

N Percent

Male 185 74

Female 65 26

Total 250 100



Designation-wise distribution of employees

Employees

N Percent

Class-1 100 40

Class-11 69 27.6

Class-111 81 32. 4

Total 250 100

Qualification wise distribution of Employees

Employees

No. Percent

Graduate 140 56

Post Graduate 110 44

Total 250 100

QUESTIONNAIRE

The questions were designed to facilitate the respondents to identify major strengths and

weakness of the Corporations and provide insights. The endeavors were to identify the key

quality of working life issues, on which employee’s perception can be obtained. The respondents

were requested specifically to ignore their personal prejudices and use their best judgment on a 5

point Likert scale. The purpose of this exercise was to make the response a true reflection of

organization reality rather than an individual opinion. The 5 point of the scale indicated in the

questionnaire are- 1. Strongly disagree, 2 disagree, 3-Undecided, 4-Agree and 5- Strongly Agree.

Reliability (Cronbach’s coefficient alpha) of the questionnaire has found to be 0.89.This shows

data has satisfactory internal consistency.

Descriptive Analysis:

Result & Discussion

The results in the following table reveal that in the scale for quality of working Life, the highest

mean score (44.29) is for male and the lowest (33.56) is for level III employees. The same has

been shown graphically in figure1.1



Summary of “t”test presented in the table 1.2 indicates that t-value (1.60) is significant as p-

value (.110) is more than 0.05.Hence the hypothesis stating the difference is not significant

between the perception of male and female employees regarding. Quality of working life is

accepted at 0.05 level of significance. So there is not a significant difference between the

perception of male and female employees regarding quality of working life.

Mean value for males (74.29) is less than females (78.89) therefore it is concluded that female

employees have better perception of QWC than male employees.

Summary of the univariate analysis of variance presented in the table 1.3 indicates that p-value

(0.232) is greater than 0.05as F value (1.469) is not significant at 0.05 level of significance.

Hence the hypothesis is accepted at 0.05 level of significance, so there is no significant

difference among the perception of employees at different levels regarding quality of working

life.

Summary of “t”test presented in the table 1.4 indicates that t-value (.348) is significant as p-

value (0.728) is more than 0.05.Hence the hypothesis stating, The difference is not significant

between the perception of graduate and post graduates employees regarding QWC. “Is accepted

at 0.05 level of significance. So there is not a significant difference between the perception of

graduate and post graduate employees regarding QWC in selected branches of LIC.

Mean value for graduate (34.69) is less than Postgraduate Employees (35.58) therefore it is

concluded that post graduate employees have better perception of QWC than graduate

employees. Thus findings are:

The difference is not significant between the perception of male and female employees regarding

quality of working life. It shows that gender does not affect the perception of QWL System of

employees as all are equally aware of the significance of it.

There is no significant difference among the perception of employees at different levels

regarding quality of working life. As all are equally aware of the significance of it. It shows that

the need of the employee’s development is felt in all cases. The difference is not significant

between the perception of Graduates and Post Graduates employees regarding the quality of

work life in selected branches of LIC. As both areas are equally related to improvement and

progress.



CONCLUSION

In LIC, Quality of Working Life principles are the principle of security, the principle of equity,

the principle of individuation and the principle of democracy. On the basis of my study I can say

that employees of LIC in Northern region are happy with the working conditions of the LIC.

They feel that they are safe and secure in LIC. They feel that corporation should start their own

transport facilities for the staff. However, the dissatisfaction among them is the less growth

opportunities. They are not provided with extra care like health camps etc Poor work life balance

leads to many disastrous things like tardy, bad performance, lack of motivation, more errors,

absence from work and so on. The worst thing is that poor work-life balance reduces work

quality and productivity without any doubt. When an employee won't be able to give time to his

family at home, he will feel stressed out at work Sound work life balance will definitely have a

positive impact on employee’s productivity. The quality of work improves significantly as

employees feel fresh and not stressed out at all.

Suggestion

1.Corporation must be committed to an open and transparent style of operation that include

sharing appropriate information with employees and sincerely inviting their input regarding

problems opportunities and implementation of improvement plans.

2. Employees must be given opportunities for advancement in the corporation.

3. Traditional status barriers between different classes must be broken to permit establishment of

an atmosphere of trust and open communication.

4. Employees should receive feed back on results achieved and recognition for superior

performance. Other forms of positive reinforcement such as financial incentives should also be

made available where feasible.

5. Improved communication and co-ordination among the workers and organization helps to

integrate different jobs resulting in better task performance.

6. Better working condition enhances workers motivation to work in a healthy atmosphere

resulting in motivation and increase in production.

7. As QWL includes participation in group discussion and solving the problem, improving the

skill, enhancing their capabilities and thus building confidence and increased output.



REFERENCES:

Anonymous (2005). Quality of Work Life Task Force looks to integrate home and work.

Vanderbilt University Medical Center, House Organ. Available from http://

www.Quality20%of/20%work/20% life. htm.

Anbarasan, V & Mehta, N. (2009), "An Exploratory Study on Perceived Quality of Working Life

among Sales Professionals Employed in Pharmaceuticals, Banking, Finance and Insurance

Companies in Mumbai", Abhigyan, 27(1): 70-81.

Ebrahim (2010) “The relation between QWL and job satisfaction”, Middle –East Journal of

scientific Research 6(4), 317-323-2010.

Feuer, D., Quality of work life: a cure for all ills? Training: The Magazine of Human Resources

Development, 26: 65-66, 1989.

Mishra, S. & Gupta, B. (2009), "Work Place Motivators and Employee's Satisfaction: A Study

on Retail Sector in India", The Journal of Industrial Relations, 44(3): 509-17.

Raduan,C. R., Loosee .B., Jegak,U & Khairuddin, I. (2006), "Quality of Work Life: Implications

of Career Dimensions", Journal of Social Sciences. 2 (2): 61-67.

Sandrick k (2003). Putting the emphasis on employees as an award. Winning employer, Baptist

health care has distant memories of the workforce shortage, Trustee. pp. 6-

Straw, R.J. and C.C. Heckscher, 1984. QWL: New working relationships in the communication

industry. Labor Studies J., Vol. 9: 261-274.

Walton, R. (1973), ― Quality of Work life Indicators- Prospects and Problems- A Portigal

Measuring the Quality of working life, pp-57-70, Ottawa



Table 1.1: Scale for Quality of working Life

Factor

No. Mean S.D

Gender-Male

185 44.29 19.85

Female

65 38.89 20.13

Designation-Level 1

100 39.27 18.69

Level 11

69 34.72 20.88

Level 111

81

33.56 22.86

Qualification-

Graduate

140 34.69 19.34

Post Graduate

110 35.58 20.95

Tab 1.2 Perceptual differences between male and female employees regarding quality of

working life.

Group Sample

size

Mean S.D. t- value df

p-value

Male

Employee

185 44.29 19.85 1.60 248 .110

Female

Employees

65 48.89 20.13

P>0.05



Tab.1.3 Perceptual differences between employees at different level regarding quality of

working life.

Particulars Sample size Mean d.f F value P value

Class-1 100 39.27 2 1.469 0.232

Class-11 69 34.72

Class-111 81 33.56

P>0.05

Tab1.4: Perceptual differences between Employees with graduate and postgraduate

qualification regarding quality of working life.

Particulars Sample Size Mean SD t-test df p-Value

Graduate

Employee

140 34.69 19.34 .348 248 .728

Postgraduate

Employees

110 35.58 20.95

P>0.05


International Journal of Research in IT, Management and Engineering

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REFACTORABILITY ANALYSIS USING LINEAR REGRESSION

Gauri Khurana*

Sonika Jindal **

ABSTRACT

Software refactoring - improving the internal structure of the software without changing its

external behavior - is an important action towards avoiding software quality decay. Key to

this activity is the identification of portions of the source code that offers opportunities for

refactoring -- the so called bad smells. The underlying objective is to improve the quality of

the software system, with regard to future maintenance and development activities. The goal

of this review paper is the discussion of an approach to help on the detection of code bad

smells through source code metrics and the results obtained from its use. In this discussion,

we propose measure of refactorability based on the four factors- reusability,

understandability, modifiability and maintainability. Since, each of the factors is intangible in

nature and is hard to measure. It is also proposed that they should be measured in terms of

point system. It is also important to bring new elements that might be affected through a

refactoring sequence as, for example, structural testing requirements that can be used in the

future as a new metric to detect refactoring opportunities.

Keywords: Refactoring, reusability, understandability, modifiability, maintainability, bad

smell, metrics

*CSE, SBSCET, Ferozpur. PTU, Jalandhar

** Assistant Professor, Department of Computer Science, SBSCET, Ferozpur. PTU,

Jalandhar.



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1. INTRODUCTION

1.1 Introduction to refactoring

Refactoring is a well-defined process that improves the quality of systems and allows

developers to repair code that is becoming hard to maintain, without throwing away the

existing source code and starting again. By careful application of refactorings the system’s

behavior will remain the same, but return to a well-structured design. The use of automated

refactoring tools makes it more likely that the developer will perform the necessary

refactorings, since the tools are much quicker and reduce chance of introducing bugs.

“Refactoring is the process of changing a software system in such a way that it does not alter

the external behavior of the code yet it improves its internal structure.”-Martin Flower in

Refactoring, Improving the Design of Existing Code.

Refactoring is a kind of reorganization. Technically, it comes from mathematics when you

factor an expression into an equivalence- the factors are cleaner ways of expressing the same

statement. Refactoring implies equivalence- the beginning and the end product must be

functionally identical. The shift from Structured Programming to Object-oriented

Programming is a fundamental example of refactoring. [1]

“Refactoring is the process of taking an object design and rearranging it in various ways to

make the design more flexible and/or usable.” – Ralph Johnson.

Four Reasons to change the code:

The four primary reasons to change the code are [2]:

1. Adding a feature

2. Fixing a bug

3. Improving the design

4. Optimizing resource usage

1.2 Preserving Behavior

Feature addition and bug fixing are very much like refactoring and optimization. In all cases

of changing code, we want to change some functionality, some behavior, but we want to

preserve much more (see Figure 1)



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Existing Behavior New Behavior

Figure 1: Preserving Behavior [2]

Figure 1 shows what is supposed to happen when we make changes, but what does it mean

for us practically? On the positive side, it seems to tell us what we have to concentrate on.

We have to make sure that small numbers of things that we change are changed correctly. On

the negative side, that isn’t the only thing we have to concentrate on. We have to figure out

how to preserve the rest of the behavior. The amount of behavior to be preserved is usually

very large.

Preserving behavior is a large challenge. When we need to make changes and preserve

behavior, it can involve considerable risk. [2] To mitigate risk, we have to ask three

questions:

1. What changes do we have to make?

2. How will we know that we’ve done them correctly?

3. How will we know that we haven’t broken anything?

1.3 Why do we need refactoring?

The longer object oriented systems are in use, the more probable it is that these systems have

to be maintained [3], i.e. they have to be optimized to a given goal (Perfective Maintenance),

they have to be corrected with respect to identified defects (Corrective Maintenance) and they

have to be adjusted to a changing environment (Adaptive Maintenance). Whereas many of

these activities can be subsumed under the reengineering area, there are additional changing

activities that are much less difficult to apply than typical reengineering activities, and which

does not change the external behavior [4]. The main goal of these “mini-reengineering

activities” is to improve the understandability and to simplify reengineering activities. Flower

calls these activities Refactorings, which he defines a “a change made to the internal

structure of a software to make it easier to understand and cheaper to modify without

changing its observable behavior” [1, p. 53].



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Fowler suggests four purposes of refactoring [1]:

1. Improve the design of software – Through accumulating code changes, code loses its

structure, thereby increasingly drifting towards a state of decay. Refactoring can be used

to cure software decay by redistributing parts of the code to the “right” places, and by

removing duplicated code. The claim that refactoring can improve the design of software

is confirmed by [3] with regard to cohesion and with respect to coupling, as indicators

for internal software quality. Another claimed benefit in the area of improved design is

improved flexibility.

2. Make software easier to understand – Refactoring can help make the code more readable

by making it better communicate its purpose. A different way in which refactoring

supports program understanding is in reflecting hypotheses about the purpose of the code

by changing the code, and afterwards testing that understanding through rerunning the

code. The suggested process to do so is to start refactoring the little details to clarify the

code, thereby exposing the design. The potential to improve understandability through

refactoring is confirmed by many authors [1, 3]. In more specific terms, [5] discusses

how refactorings can be used to improve communicating the purpose of the code.

3. Help find bugs – Through clarifying the structure of the code, the assumptions within the

code are also clarified, making it easier to find bugs.

4. Program faster – Through improving the design and overall understandability of the

code, rapid software development is supported.

1.4 When should one consider refactoring?

Ideally, refactoring would be part of a continuing quality improvement process. In other

words, refactoring would be seamlessly interwoven with other day-to-day activities of every

software developer.

Refactoring may be useful, when a bug has surfaced and the problem needs to be fixed or the

code needs to be extended. Refactoring at the same time as maintenance or adding new

features also makes management and developers more likely to allow it, since it will not

require an extra phase of testing.

If the developer in charge finds it difficult to understand the code, he will (hopefully) ask

questions, and begin to document the incomprehensible code.

Often, however, schedule pressures do not permit to implement a clean solution right away.

A feature might have to be added in a hurry, a bug patched rather than fixed. In these cases,



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the code in question should be marked with a FIXME note, in order to be reworked, when

time permits. Such circumstances call not for individual refactorings, but for a whole

refactoring project. When the time has come to address the accumulated problems, a scan for

FIXMEs, TODOs, etc. over the code base will return all the trouble spots for review. They

can be refactored according to priority.

2. SEMANTIC GAP

The concept of Semantic gap is relevant whenever a human activity, observation and task are

transferred into computational representation [6]. Like programs, programming languages are

not only mathematical objects but also software engineering artifacts. Describing the

semantics of real-world languages can help bring language theory to bear on both exciting

and important real-world problems. Achieving this is not purely a mathematical task, but

equally one of (semantic) engineering. The implementations of all major languages—

especially scripting languages defined by implementations—come with large and well-

structured test suites. These suites embody the intended semantics of the language. We

should be able to use such a test suite to retrofit semantics. For this to be useful, it is not

sufficient to merely create semantics for the core language [4].

More precisely the gap means the difference between contextual knowledge in a

powerful language (e.g. natural language) and its reproducible and computational

representation in a formal language (e.g. programming language).

The semantic gap actually opens between the selection of the rules and the representation

of the task.

With the passage of time, the business scenario keeps on changing and the software

development must match the business environment. Therefore the code of any software also

changes with respect to the business scenario. There might be architectural changes in

software due to business reengineering process. The programmer has to rethink how to do the

implementation of the code due to changes in the requirements. So, it offers opportunity to

relook, redesign, as well as refactor the code. Thus, it forces new semantics to be laid with

respect to the changing business scenario.

3. REFACTORING ACTIVITIES

The refactoring process consists of a number of different activities, each of which can be

automated to a certain extent [7]:



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1. Identify where the code should be refactored;

2. Determine which refactorings should be applied to the identified places;

3. Guarantee that the applied refactoring preserves behavior;

4. Apply the refactoring;

5. Assess the effect of refactoring on software quality characteristics;

6. Maintain consistency between refactored program code and other software artifacts (or

vice versa).

The steps taken when applying the refactoring should be small enough to oversee the

consequences they have and reproducible to allow others to understand them. Generalized

refactoring steps in away, are mere a rule that can be applied to any structure.

Refactoring not only covers the mechanics of restructuring, but also addresses the following

issues [Martin Flower]:

1. Refactoring emphasizes that, in absence of more formal guarantees, testing should be

used to ensure that each restructuring is behavior preserving. A rich test suite should be

built, which must be run before and after each test is applied.

2. Refactorings are described in a catalog, using a template reminiscent of design patterns.

3. Refactorings are applied in small steps, one by one, running the test suite after every step

to make it into commercial development tools.

4. METRICS FOR REFACTORABILITY

The various metrics are identified for calculating the values of four factors proposed here

separately. Those are defined as follows:

1. LinesOfCode (NbLines): The LOC for a method is equals to the number of sequence

point found for this method in the file. A sequence point is used to mark a spot in the

IL code that corresponds to a specific location in the original source. Notice that

sequence points which correspond to braces ‘‘ and ‘’ are not taken into account.

Interfaces, abstract methods and enumerations have a LOC equals to 0. Only concrete

code that is effectively executed is considered when computing LOC.



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Namespaces, types, fields and methods declarations are not considered as line of code

because they don’t have corresponding sequence points.

LOC computed from an anonymous method doesn’t interfere with the LOC of its

outer declaring methods.

Recommendations: Methods where LinesOfCode is higher than 20 are hard to

understand and maintain. Methods where ILInstructions is higher than 40 are

extremely complex and should be split in smaller methods (except if they are

automatically generated by a tool).

2. LinesOfComment(NbComments): This metric can be computed only if PDB files

are present and if corresponding source files can be found. The number of lines of

comment is computed as follow:

For a method, it is the number of lines of comment that can be found in its body. If a

method contains an anonymous method, lines of comment defined in the anonymous

method are not counted for the outer method but are counted for the anonymous

method.

For a type, it is the sum of the number of lines of comment that can be found in each

of its partial definition.

For a namespace, it is the sum of the number of lines of comment that can be found in

each of its partial definition.

For an assembly, it is the sum of the number of lines of comment that can be found in

each of its source file.

Notice that this metric is not an additive metric (i.e. for example, the number of lines of

comment of a namespace can be greater than the number of lines of comment over all its

types).

Recommendations: This metric is not helpful to asses the quality of source code. We

prefer to use the metric PercentageComment.

3. NbMethods: The number of methods. A method can be an abstract, virtual or non-

virtual method, a method declared in an interface, a constructor, a class constructor, a

finalizer, a property/indexer getter or setter, an event adder or remover.

Recommendations: Types where NbMethods > 20 might be hard to understand and



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maintain but there might be cases where it is relevant to have a high value for

NbMethods.

4. NbFields: The number of fields. A field can be a regular field, an enumeration's value

or a read only or a const field.

Recommendations: Types that are not enumeration and where NbFields is higher 20

might be hard to understand and maintain but there might be cases where it is relevant

to have a high value for NbFields.

5. Afferent coupling (Ca): The number of types outside this assembly that depend on

types within this assembly. High afferent coupling indicates that the concerned

assemblies have many responsibilities.

6. Efferent coupling (Ce): The number of types outside this assembly used by child

types of this assembly. High efferent coupling indicates that the concerned assembly

is dependant.

There is a whole range of interesting code metrics relative to coupling. The simplest

ones are named Afferent Coupling (Ca) and Efferent Coupling (Ce). Basically, the

Ca for a code element is the number of code elements that use it and the Ce is the

number of code elements that it uses.

Figure 2: Afferent and Efferent Coupling

You can define Ca and Ce for the graph of assemblies dependencies, the graph of

namespaces dependencies, the graph of types dependencies and the graph of methods

dependencies of a code base. You can also define the Ca metric on the fields of a

program as the number of methods that access the field.



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7. Cyclomatic Complexity (CC): Cyclomatic complexity is a popular procedural

software metric equal to the number of decisions that can be taken in a procedure.

Concretely, in C# the CC of a method is 1 + the number of following expressions

found in the body of the method :

if | while | for | foreach | case | default | continue | goto | && | || | catch | ternary

operator? : | ??

Following expressions are notcounted for CC computation:

else | do | switch | try | using | throw | finally | return | object creation | method call |

field access

The Cyclomatic Complexity metric is defined on methods. Adapted to the OO world,

this metric is also defined for classes and structures as the sum of its methods CC.

Notice that the CC of an anonymous method is not counted when computing the CC

of its outer method.

Recommendations: Methods where CC is higher than 15 are hard to understand and

maintain. Methods where CC is higher than 30, are extremely complex and should be

split in smaller methods (except if they are automatically generated by a tool).

8. Efferent coupling at method level (MethodCe): The Efferent Coupling for a

particular method is the number of methods it directly depends on.

9. Afferent coupling at field level (FieldCa): The Afferent Coupling for a particular

field is the number of methods that directly use it.

10. NbOverloads: The number of overloads of a method. . If a method is not overloaded,

its NbOverloads value is equals to 1. This metric is also applicable to constructors.

Recommendations: Methods where NbOverloads is higher than 6 might be a problem

to maintain and provoke higher coupling than necessary. This feature helps reducing

the number of constructors of a class.

11. Association Between Classes (ABC): The Association between Classes metric for a

particular class or structure is the number of members of others types it directly uses

in the body of its methods.

12. Depth of Inheritance Tree (DIT): The Depth of Inheritance Tree for a class or a

structure is its number of base classes (including the System.Object class thus DIT >=



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1).

Recommendations: Types where DepthOfInheritance is higher or equal than 6 might

be hard to maintain. However it is not a rule since sometime your classes might

inherit from third-party classes which have a high value for depth of inheritance.

13. NbAssemblies: Only application assemblies are taken into account.

14. NbNamespaces: The number of namespaces. The anonymous namespace counts as

one. If a namespace is defined over N assemblies, it will count as N.

15. PercentageCoverage: The percentage of code coverage by tests. Code coverage data

are imported from coverage files. If you are using the uncoverable attribute feature on

a method for example, if all sibling methods are 100% covered, then the parent type

will be considered as 100% covered. Coverage metrics are not available if the metric

LinesOfCode is not available.

Recommendations: The closer to 100%, the better.

16. Relational Cohesion (H): Average number of internal relationships per type. Let R

be the number of type relationships that are internal to this project (i.e. that do not

connect to types outside the project). Let N be the number of types within the project.

H = (R + 1)/ N. The extra 1 in the formula prevents H=0 when N=1. The relational

cohesion represents the relationship that this project has to all its types.

Recommendations: As classes inside an project should be strongly related, the

cohesion should be high. On the other hand, too high values may indicate over-

coupling. A good range for RelationalCohesion is 1.5 to 4.0. Projects where,

RelationalCohesion < 1.5 or RelationalCohesion > 4.0 might be problematic.

5. RATING SCALE

A rating scale is a set of categorize designed to elicit information about a quantitative or a

qualitative attribute. In the social sciences, common examples are the Likert scale and 1-10

rating scales in which a person selects the number which is considered to reflect the

perceived quality of a product. More than one rating scale is required to measure an attitude

or perception due to the requirement for statistical comparisons between the categories in the

polytomous Rasch model for ordered categories (Andrich, 1978).

5.1 Likert scale



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A Likert scale is a psychometric scale commonly used in questionnaires, and is the most

widely used scale in survey research, such that the term is often used interchangeably with

rating scale even though the two are not synonymous. When responding to a Likert

questionnaire item, respondents specify their level of agreement to a statement. The scale is

named after its inventor, the US organizational-behavior psychologist Rensis Likert (1903-

81). Each item may be analyzed separately or in some cases item responses may be summed

to create a score for a group of items. Hence, Likert scales are often called summative scales.

Likert scale data can, in principle, be used as a basis for obtaining interval level estimates on

a continuum by applying the polytomous Rasch model, when data can be obtained that fit this

model. In addition, the polytomous Rasch model permits testing of the hypothesis that the

statements reflect increasing levels of an attitude or trait, as intended. For example,

application of the model often indicates that the neutral category does not represent a level of

attitude or trait between disagree and agree categories. Again, not every set of Likert scaled

items can be used for Rasch measurement. The data has to be thoroughly checked to fulfill

the strict formal axioms of the model.

Likert scales usually have five potential choices (strongly agree, agree, neutral, disagree,

strongly disagree) but sometimes go up to ten or more. The final average score represents

overall level of accomplishment or attitude toward the subject matter [8].

Since, each of the factors is intangible in nature and is hard to measure. It is also proposed

that they should be measured in terms of point system as follows:

Table 1: Scale of Reusability:

High Reusability 10-9

Medium Reusability 8-7

Low Reusability 6-5

Very low Reusability 4-3

No Reusability 2-1



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Table 2: Scale of Maintainability:

High Maintainability 10-9

Medium Maintainability 8-7

Low Maintainability 6-5

Very low Maintainability 4-3

No Maintainability 2-1

Table 3: Scale of Understandability:

High Understandability 10-9

Medium Understandability 8-7

Low Understandability 6-5

Very low Understandability 4-3

No Understandability 2-1

Table 4: Scale of Modifiability:

High Modifiability 10-9

Medium Modifiability 8-7

Low Modifiability 6-5

Very low Modifiability 4-3

No Modifiability 2-1



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6. CORRELATION AND REGRESSION ANALYSIS

Correlation and regression are generally performed together. The application of correlation

analysis is to measure the degree of association between two sets of quantitative data. There

are virtually no limits of applying correlation analysis to any dataset of two or more variables.

It is the researcher’s responsibility to ensure correct use of correlation analysis. Correlation is

usually followed by regression analysis in many applications. The main objective of

regression analysis is to explain the variation in one variable (called the dependent variable),

based on the variation in one or more other variables (called the independent variables). If

there are only one dependent variable and only one independent variable used to explain the

variation in it, then the model is known as simple regression. If multiple independent

variables are used to explain variation in one dependent variable, it is called multiple

regressions [9]. Even though the regression equation could be either linear or non-linear, we

limited our discussion to linear models.

From the regression analysis of the various four factors (reusability, understandability,

modifiability, maintainability) separately, using their respective metrics, the analysis of

refactorability can be done by applying linear regression over refactorability using these four

factors. Thus, the regression equation for refactorability will be as follows:

Y=a+bX1+cX2+dX3+eX4

Where, Dependent Variable= Y

Independent Variables are: X1, X2, X3, and X4.

The above mentioned regression equation is applied to each factor that is considered to be

affecting the refactorability of the software. The underlying steps are carried out for each of

the factor separately, by considering their respective metrics as their independent variables.

Step 1: Collect the dataset containing the values for each metric identified. And based on that

dataset, the points based on the rating scale are assigned, considering the rules.

Step 2: The correlation is found among the independent variables and dependent variables,

for each factor affecting refactoring. The SPSS 16 tool is used to find the correlation. The

positive value of correlation specifies that the factor is directly affected by that variable. And,

the negative value shows that the factor is inversely affected by the respective variable.



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Step 3: The regression analysis is done to explain the variation in one variable (dependent

variable), based on the other variable (independent variable). The linear equation is used for a

regression analysis and the values of the coefficients of the linear equation are determined.

Step 4: The output of the regression is determined with the help of value of R-square. The

measure of strength of association in the regression analysis is given by the determination of

R-square. The coefficient varies between 0 and 1 and represents the proportion of total

variation in the dependent variable that is accounted by the variation in the factors.

After applying all the steps to each factor, the refactorability is estimated using the linear

regression equation, considering refactorability as the dependent variable and other four

factors affecting refactoring as independent variables. The partial regression plots are

obtained for each factor, the slope of which determines that the model designed to determine

the refactorability is good or bad. The linear slope of the graph determines that the model

developed for refactorability based on that factor is good enough to determine the

refactorability.

The results of the regression analysis of all the factors, considered, that affect refactoring are

studied. Based on the results of each factor the points on the Rating scale are obtained for

refactorability.

7. CONCLUSION

Software Refactoring is an important area of research that promises substantial

benefits to software maintenance. Refactoring is a process that improves the

quality and allows developers to repair code that is becoming hard to maintain,

without throwing away the existing source code and starting again. We can return

with a well structured and well designed code after proper application of

refactoring techniques. By careful application of refactorings the system’s behavior will

remain the same, but return to a well-structured design. The use of automated refactoring

tools makes it more likely that the developer will perform the necessary refactorings, since

the tools are much quicker and reduce chance of introducing bugs.

From the literature survey of various research papers, the following factors are determined for

measuring refactoring of code and level of optimization of code namely- reusability,

maintainability, understandability, modifiability. Here, we have proposed a 10-point system,

to measure refactorability. The 10-point system is based on the Likert’s Rating Scale. The



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metrics that affect each factor of refactoring are determined and the values are calculated.

The correlation and regression analysis is performed to determine the associations and

variations among the various metrics used and their respective factors. The linear regression

equation for applying regression analysis used is given as

Y=a + bX1 + cX2 + dX3 + eX4

Where, Y= dependent variable, a, b, c, d, e are correlation coefficients, and X1, X2, X3, X4

are independent variables. The variation in independent variables affects the variation in

dependent variable.The measure of strength of association in the regression analysis is given

by the coefficient of determination, denoted by R-square. The coefficient varies between 0

and 1 and represents the proportion of total variation in the dependent variable that is

accounted for, by the variation in the factors.

REFERENCES

[1] Martin Flower, Kent Beck, John Brant, William F. Opdyke, Don Roberts, 1999,

Refactoring: Improving the Design of Existing Code, Addison Wesley.

[2] Robert C. Martin Series, 2004, Working Effectively with Legacy Code, Michael C.

Feathers, Prentice Hall.

[3] Frank Simon, Frank Steinbruckner, Claus Lewerentz, 2001, Metrics Based Refactorings,

In: Proceedings of 5th European Conference on Software Maintenance and Reengineering,

IEEE CS Press, Lisbon, Portugal, pp. 30-38.

[4] Arjun Guha, Shriram Krishnamurthi, 2010, Minding the (Semantic) Gap, Engineering

Programming Language Theory.

[5] W. C. Wake, 2003. Refactoring Workbook, Addison-Wesley Longman Publishing Co.,

Inc., Boston, MA, USA.

[6] C. Dorai, S. Venkatesh, 2003. Bridging the Semantic Gap with Computational Media

Aesthetics, IEEE Multimedia, Vol. 10, No. 2, pp.15-17.

[7] Tom Mens, Tom Tourwe, 2004, A Survey of Software Refactoring, IEEE Transactions on

Software Engineering, Vol. 30, No. 2, pp. 126-139.

[8] http://www.businessdictionary.com/definition/Likert-scale.html

[9] John Fox, 1997, Applied Regression Analysis, Linear Models, and Related Methods,

Thousands Oaks, CA: Sage Publications.



www.gjmr.org

38

OPTIMIZING FILTERING PHASE FOR NEAR-DUPLICATE

DETECTION OF WEB PAGES USING TDW-MATRIX

Tanvi Gupta*

ABSTRACT

The voluminous amount of web documents has weakened the performance and reliability of

web search engines. Web content mining face huge problems due to the existence of duplicate

and near-duplicate web pages. These pages either increase the index storage space or

increase the serving costs thereby irritating the users. In this paper, the proposed work is to

optimize the filtering phase consists of prefix and positional filtering by adding suffix filtering

which is a generalization of positional filtering to the suffixes of the records. The goal is to

add one more filtering method that prunes candidates that survive the prefix and positional

filtering.

Keywords: near-duplicates, TDW-matrix, Prefix-filtering, Positional-filtering, suffix-filtering

*Lingaya’s University, Faridabad, India



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39

INTRODUCTION:

Over the last decade there is tremendous growth of information on World Wide Web

(WWW).It has become a major source of information. Web creates the new challenges of

information retrieval as the amount of information on the web and number of users using web

growing rapidly. It is practically impossible to search through this extremely large database

for the information needed by user. Hence the need for Search Engine arises. Search Engines

uses crawlers to gather information and stores it in database maintained at search engine side.

For a given user's query the search engine searches in the local database and very quickly

displays the results.

But, the voluminous amount of web documents has resulted in problems for search engines

leading to the fact that the search results are of less relevance to the user. In addition to this,

the presence of duplicate and near-duplicate web documents has created an additional

overhead for the search engines critically affecting their performance. The demand for

integrating data from heterogeneous sources leads to the problem of near-duplicate web

pages. Near-duplicate data bear high similarity to each other, yet they are not bitwise

identical [2][4].

A. TDW Matrix Algorithm

TDW Matrix Algorithm is a three-stage algorithm which receives an input record and a threshold

value and returns an optimal set of near-duplicates. In first phase, rendering phase[3], all pre-

processing are done and a weighting scheme is applied. Then a global ordering is performed to form a

term-document weight matrix. In second phase, filtering phase, two well-known filtering mechanisms,

prefix filtering and positional filtering, are applied to reduce the size of competing record set and

hence to reduce the number of comparisons. In third phase, verification phase, singular value

decomposition is applied and a similarity checking is done based on the threshold value and finally

we get an optimal number of near-duplicate records.



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40

Fig.1: General Architecture [1].

B. Suffix Filtering Method:-

Suffix filtering method, is a generalization of the positional filtering to the suffixes of the

records. However, the challenge is that the suffixes of records are not indexed nor their partial

overlap has been calculated. Therefore, we face the following two technical issues:

(i) How to establish an upper bound in the absence of indices or partial overlap results?

(ii) How to find the position of a token without tokens being indexed?

The first issue is solved by converting an overlap constraint to an equivalent Hamming

distance constraint. Then lower bound the Hamming distance by partitioning the suffixes in a

coordinated way. The suffix of a record x is denoted as xs. Consider a pair of records,

(x, y), that meets the Jaccard similarity threshold t, and without loss of generality, |y| ≤ |x|.

Since their overlap in their prefixes, is at most the minimum length of the prefixes, the

following upper bound can be derived in terms of the Hamming distance of their suffixes.

H (xs, ys) ≤ Hmax =2|x| − 2 t/1 + t ・ (|x| + |y|) − ( t ・ |x| − t ・ |y| ) –(1)

In order to check whether H (xs, ys) exceeds the maximum allowable value, an estimate of the

lower bound of H (xs, ys) is provided below. First we choose an arbitrary token w from ys,



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41

and divide ys into two partitions: the left partition yl and the right partition yr. The criterion

for the

partitioning is that the left partition contains all the tokens in ys that precede w in the global

ordering and the right partition contains w (if any) and tokens in ys that succeed w in the

global ordering. Similarly, divide xs into xl and xr using w too (even though w might not

occur in x). Since xl (xr) shares no common token with yr (yl), H(xs, ys) = H(xl, yl) + H(xr, yr).

The lower bound of H (xl, yl) can be estimated as the difference between |xl| and |yl|, and

similarly for the right partitions. Therefore,

H (xs, ys) ≥ abs (|xl| − |yl|) + abs (|xr| − |yr|) -(2)

Finally, we can safely prune away candidates whose lower bound Hamming distance is

already larger than the allowable threshold Hmax.

RELATED WORK:

A .Prefix Filtering: Consider an Ordering O of the token universe U and a set of records,

each with tokens sorted in the order of O. Let the p-prefix of a record x be the first p tokens

of x. If O(x, y) ≥ α, then the (|x|−α+1)-prefix of x and the (|y|−α+1)-prefix of y must share at

least one token.

Prefix filtering is a necessary but not sufficient condition for the corresponding overlap

constraint, an algorithm is designed as: first build inverted indices on tokens that appear in

the prefix of each record in an indexing phase. Then generate a set of candidate pairs by

merging record identifiers returned by probing the inverted indices for tokens in the prefix of

each record in a candidate generation phase. The candidate pairs are those that have the

potential of meeting the similarity threshold and are guaranteed to be a superset of the final

answer due to the prefix filtering principle. Finally, in a verification phase, evaluate the

similarity of each candidate pair and add it to the final result if it meets the similarity

threshold.

B. Positional Filtering: Consider an ordering O of the token universe U and a set of

records, each with tokens sorted in the order of O. Let token w = x[i], w partitions the record

into the left partition xl (w) = x [1 . . . (i − 1)] And the right partition xr(w) = x[i . . |x|]. If O(x,

y) ≥ α, then for every token w x ∩ y, O (xl (w), yl(w)) + min(|xr(w)|, |yr(w)|) ≥ α.



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42

A natural idea to utilize the positional filtering principle is to combine it with the existing

prefix filtering method, which already keeps tracks of the current overlap of candidate pairs

and thus gives us O (xl (w), yl(w)).

PROPOSED WORK:

Here, I have proposed an idea of adding one more filtering technique suffix filtering , which

is a generalized form of positional filtering which will further reduce the candidate pairs size,

which helps in much more efficient way to detect near-duplicates.

In this new architecture, there are three phases:

1) Rendering Phase

2) Filtering Phase

3) Verification Phase

Rendering Phase consists of (i) Preprocessing which includes tokenization, stemming, and

stop word removal. Then (ii) Feature Weighting is done according to the proposed scheme

given in Ref.[1] on the preprocessed data .After that, (iii) Canonicalization[1]., is done. The

final result of this phase is the TDW Matrix [1].

Filtering Phase includes (i) Prefix Filtering, the basic idea behind this filtering principle is

that if two web pages share rare tokens, there is a chance that it might be similar. Since a

global ordering is done based on document frequencies, prefix set of a record contain rare

tokens. If no tokens are shared in prefix set, that record can be avoided from further

processing. Once prefix filtering is over, (ii) positional filtering principle[2]. is applied in

order to prune unwanted records from candidate set C. (iii) Finally, suffix filtering[2]. is done

on the candidate pairs come from positional filtering, which uses hamming distance

constraint(Hmax) instead of overlap constraints . The suffix of a record x is denoted as xs.

Consider a pair of records, (x, y), that meets the Jaccard similarity threshold t, and without

loss of generality, |y| ≤ |x|. Since their overlap in their prefixes, is at most the minimum length

of the prefixes, the upper bound can be derived in terms of the Hamming distance of their

suffixes.

H (xs, ys) ≤ Hmax =2|x| − 2 t/1 + t ・ (|x| + |y|) − ( t ・ |x| − t ・ |y| )

In order to check whether H (xs, ys) exceeds the maximum allowable value, an estimate of the

lower bound of H (xs, ys) is provided below. The lower bound of H(xl, yl) can be estimated as

the difference between |xl| and |yl|, and similarly for the right partitions. Therefore,

H (xs, ys) ≥ abs (|xl| − |yl|) + abs (|xr| − |yr|) -



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43

Finally, we can safely prune away candidates whose lower bound Hamming distance is

already larger than the allowable threshold Hmax.

Based on the records from mezzanine set M, a weight matrix A is created such that columns

represent documents and rows represent terms. An element aij represents the weight of the

global feature xi in record rj-1 since the first column represents input record r. In verification

phase, (i) singular value decomposition is applied on weight matrix A and each record can be

represented as a vector in 2D space. Then Jaccard threshold 0 ≤ t ≤1, can be mapped into an

angle 180 ≥ θ ≥ 0 accordingly, using the formula

θ =180*(1 – t) - (3)

We can say that two records are purely dissimilar when the angle between them is 180 and

they are exactly similar if it is 0.

Ultimately we get an optimum set of records by analyzing the angle of a document with

respect to input record r. If it satisfies the threshold θ, it can be marked as a near- duplicate of

r and ranked on the basis of angle.

Fig. 2 :

Optimizing filtering phase in general architecture

Proposed Algorithm for filtering Phase

Input: TDW_Matrix,Record_Set,t

Output: M

t- Jaccard Threshold -Angle

O- Overlap Threshold C- Candidate Set

Hmax- Hamming Constraint M- Mezzanine Set

O*- Optimal set



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44

Remarks: Assume that Input_Record is represented as the first entry in TDW_Matrix

Filtering (TDW_Matrix, Record_Set, t)

r←TDW_Matrix[1];

//prefix filtering

C← φ;

Prefix_Length← |r|- t.|r| +1;

for all ri Record_Set

Prefixi←|ri|- t.|ri| +1;

for all j,k; 1≤ j ≤ Prefix_Length, 1≤ k ≤ Prefixi

if (r[j] == ri[k])

C← C ri;

//positional filtering

M1← φ;

for all ri C

O← t/t+1(|r|+|ri|);

for all p,q; 1≤ p ≤ Prefix_Length, 1≤ q ≤ Prefixi

if (r[p]==ri[q])

ubound←1+ min(|r|-p, |ri|-q);

if (ubound ≥ O)

M1← M1 ri;

return M1;

// suffix filtering /* x and y are tokens*/

SuffixFilter(x, y, Hmax, d)

M← φ

if d > MAXDEPTH then return abs(|x| − |y|) ; /*d-> current recursive depth*/

mid ← |y| /2 ; w ← y[mid];

o ← (Hmax−abs(|x|−|y|))/2 /* always divisible */;

if |x| < |y| then ol ← 1, or ← 0 else ol ← 0, or ← 1;

(yl, yr, f, diff) ← Partition(y,w,mid,mid);

(xl, xr, f, diff) ← Partition(x,w,mid −o − abs(|x| − |y|) ・ ol, mid + o + abs(|x| − |y|) ・ or);

if f = 0 then

return Hmax + 1

H ← abs(|xl| − |yl|) + abs(|xr| − |yr|) + diff;



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45

if H > Hmax then

return H

else

Hl ←SuffixFilter(xl, yl,Hmax−abs(|xr|−|yr|)−diff, d+1) ;

H ← Hl + abs(|xr| − |yr|) + diff;

if H ≤ Hmax then

Hr ← SuffixFilter(xr, yr,Hmax − Hl − diff, d + 1) ;

return Hl + Hr + diff

else

return H, M← M ri;

//partition / *s is the set of tokens and its two subsets are sl and sr */

Partition(s,w, l, r)

sl ← φ ; sr ← φ;

if s[l] > w or s[r] < w then

return ( φ, φ, 0, 1)

p ← binary search for the position of the first token in s that is no smaller than w in the

global ordering within s[l . . r];

sl ← s[1 . . p − 1];

if s[p] = w then

sr ← s[(p + 1) . . |s|]; /* skip the token w */;

diff ← 0;

else

sr ← s[p . . |s|];

diff ← 1;

return (sl, sr, 1, diff)

CONCLUSION AND FUTURE WORK

In this paper, the proposed work is to add one more filtering method in filtering phase named

suffix filtering which is a generalization of positional filtering which will further reduce the

candidate sizes. Both, positional filtering and suffix filtering are complementary to the

existing prefix filtering technique. They successfully alleviate the problem of quadratic

growth of candidate pairs when the data grows in size. So, this will further improve the



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46

method to detect near-duplicates. Further research works can extend this to a more efficient

method for finding similarity joins which can be incorporated in a focused w

REFERENCES:

[1] Midhun Mathew, Shine N Das ,TR Lakshmi Narayanan, Pramod K Vijayaraghvan, A

Novel Approach for Near-Duplicate Detection of Web Pages using TDW Matrix. (IJCA, vol

19-no.7,April 2011)

[2] Chuan Xiao, Wei Wang, Xuemin Lin , Jeffrey Xu Yu, Efficient Similarity Joins for Near

Duplicate Detection, Proceeding of the 17th international conference on World Wide Web, pp

131 – 140. April 2008.

[3] Shine N Das, Midhun Mathew, Pramod K.Vijayaraghavan, An Approach for Optimal

Feature Subset Selection using a New Term Weighting Scheme and Mutual Information,

Proceeding of the International Conference on Advanced Science, Engineering and

Information Technology, Malaysia, 2011, pp 273-278, January 2011.

[4] Gurmeet Singh Manku, Arvind Jain and Anish Das Sarma, Detecting near-duplicates for

web crawling, In Proceedings of the 16th international conference on World Wide Web, pp.

141 - 150, Banff, Alberta, Canada, 2007.

.



STUDY AND DESIGN OF BUILDING INTEGRATED PHOTO

VOLTAIC SYSTEM AT HCTM CAMPUS KAITHAL, HARYANA

Rajeev Kumar*

Gagan Deep Singh**

ABSTRACT

The depletion of fossil fuel resources on a worldwide basis has necessitated an urgent search

for alternative energy sources to meet up the present day demands. Solar energy is clean,

inexhaustible and environment-friendly potential resource among renewable energy options.

But neither a standalone solar photovoltaic system nor a wind energy system can provide a

continuous supply of energy due to seasonal and periodic variations. Therefore, in order to

satisfy the load demand, grid connected energy systems are now being implemented that

combine solar and conventional conversion units. The objective of this work is to estimate the

potential of grid quality solar photovoltaic power in HCTM Campus, Kaithal district of

Haryana and finally develop a system based on the potential estimations made for a chosen

area. Equipment specifications are provided based on the availability of the components in

India. Annual energy generation by proposed Grid connected SPV power plant is also

calculated. In the last, cost estimation and payback analysis of grid connected SPV power

plant is done to show whether it is economically viable or not.

Keywords: diurnal variations, daily energy output, monthly energy output, grid connected

photovoltaic (PV) system, PWM inverters, solar radiation, yearly energy output.

*Department of Electrical and Electronics Engineering, Haryana College of Engineering and

Technology, Kaithal, Haryana

**Department of Electrical Engineering, Guru Nanak Dev Engineering College, Ludhiana, Punjab



1. INTRODUCTION

Electricity is obtained from the PV array most efficiently during daytime. But at night or

during cloudy periods, independent power systems use storage batteries to supply the

electricity needs. With grid interactive systems, the grid acts as the battery, supplying

electricity when the PV array cannot. The energy storage devices viz. battery has been

avoided in this work. This approach reduces the capital as well as the running cost. We have

tried to develop a grid connected photovoltaic system. Grid connected photovoltaic system is

well known in various parts of world, and several technologies are used. There have been

efforts to develop the power electronics circuitry involved. Several types of inverters have

been designed. But our focus is to obtain the potential of grid connected photovoltaic system

in Kaithal district of Haryana and finally develop a system based on the potential estimations

made for a chosen area. Equipment specifications are provided based on the availability of

the components in India. Annual energy generation by proposed Grid connected SPV power

plant is also calculated. In the last, cost estimation and payback analysis of grid connected

SPV power plant is done to show whether it is economically viable or not.

2. METHODOLOGY

To find out the solar potential available at Kaithal district of Haryana, reading of solar

radiation for site is required. So these readings are taken from HAREDA, Sec-26 Chandigarh.

The data for solar radiation for Kaithal district of Haryana is shown in table 1

Table 1 Comparison of average solar insolation data kwhr/m2/day of district Kaithal

Months HARSAC NASA % Deviation

Jan. 2.76 3.58 22.9

Feb. 4.15 4.38 5.25

March 4.86 5.59 13

April 6.24 6.1 2.2

May 5.86 6.4 8

June 5.04 6.2 18

July 4.6 5.5 16

Aug. 4.47 5.14 13

Sep. 4.5 5.23 13



Oct. 4.85 4.71 2.9

Nov. 3.42 4.01 14

Dec. 2.53 3.36 24

Annual 4.44 5.02 11

HARSAC: Average values from January 2003 to December 2007

NASA: Average values from July 1983 to June 2005

Graph 1

So, in order to design building integrated PV system in HCTM campus, district Kaithal, the

average of annual solar insolation in district Kaithal measured by two agencies i.e. HARSAC

and NASA is taken.

According to HARSAC, annual solar insolation in Kaithal = 4.44 kwhr/m2/day.

According to NASA, annual solar insolation in Kaithal = 5.02 kwhr/m2/day.

So, average annual solar insolation in Kaithal = (4.44 + 5.02)/2 = 4.73

kwhr/m2/day.

= 4.73/6 =

788.333w/m2/day.

Efficiency of solar panel = 14.3%

So, average peak output

= 788.3×0.143 = 112.73 W/m2

0

2

4

6

8

solar insolation in

Kwh/m

2

Graph for monthly peak variation in Kaithal



Table 2 Load calculation of block A

Fan load

(KW)

Tube Lights

load (KW)

6A/3pinsocket load

(KW)

Coolers

load

(KW)

Computers load

(KW)

Total

load

(KW)

262 × 80 =

20.96

286 × 40 =

11.44

77 × 40 = 3.08 6 × 300 =

1.8

26 × 300 = 7.8

45.08

Total load of A-Block = 45.08 KW

Roof Area of Block A

Length = 358 ft = 109.14 m; Breadth = 58 ft = 17.68 m

Roof area = 109.14 × 17.68 = 1929.59 m2

3. ENERGY CALCULATION

Table 3 Energy generated from Block A

Name

of

Block

Available

Area (m2)

Area

used

(m2)

Average

Peak

Output

(W/m2)

Possible

Plant

Capacity

(KW)

Energy

Generated

per day

(KW-hr)

Energy

Generated

per month

(KW-hr)

A 1929.59 400 112.73 45 270 8100

4. SYSTEM SIZING

Table 4 Solar Panel Specification

Watt 180 Watt

Voltage 24 Volts

Current 7.5 A

Type Polycrystalline

Efficiency 14.3%

IJRIME

The wirin

PWM inv

The calcu

Phase vo

Line volt

KVA rati

E

Interna

Temperat

Dimensio

Tilt angle

Mounting

ng diagram o

verters are u

ulation for fi

oltage= Vph=

tage = VL =

ing = KW ×

ational Journ w

ture

ons (mm)

e(slope) of PV

g

of PV array

Fig

used for supp

inding the ou

= 0.4714 × V

0.779 × Vdc

assumed po

Volum

al of Researcww.gjmr.org

V Module

is shown in

gure 1 wiring

pressing the

utput voltage

Vdc= 0.4714

= 0.779× 2

ower factor =

me1Issue5

h in IT, Mana

25 deg c

1593 × 790

Area of sing

Area of sing

45 degree

Fixed Type

Figure 1

g diagram of

harmonics p

e of inverter

4× 240= 113.

240 = 187 V

= KW × 0.8

5

gement and

× 50

gle panel = 1

gle panel = 1

f PV array

produced aft

r is shown be

.136 Volts.

Volts.

ISSN‐22

Engineering

1258470 (mm

1.259 meter²

ter DC to AC

elow: [26]

249‐ 161

m)

²

C Conversion

9

n.



Table 5 Solar Photovoltaic Power Plant Specification

Plant Capacity 45 KW

Voltage Output 240 Volts dc

Current Output 187.5 A

No. of Modules 250

Area 400 m2

Table 6 Inverter Specification

KVA rating 36 KVA

Input DC voltage 240Volts DC

Input dc current 187.5A

Output AC voltage 113.136 V ac (phase voltage)

187 V ac (line voltage)

No. of Phases 3-φ

Type PWM (for suppressing 3rd harmonics)

Efficiency Almost 90-95%

Total harmonic distortion < 5%

Table 7 Transformer Specification

KVA rating 36 KVA

No of phases 3-φ

Frequency rating 50 Hz

Primary voltage rating 187 V

Secondary voltage rating 400 V

Primary current rating 192.51 A

Secondary current rating 90A

Connections Primary – delta (for

suppressing3rd harmonics)

Secondary – star



10 to 25 taps in secondary

Efficiency Almost 95 %

Extra features Air cooled

5. COST ANALYSIS FOR 45 KW SOLAR PV PLANT:

1.Cost of solar panels: - The BP 7180 most powerful module manufactured by BP Solar is

used; cost of solar panel is Rs.160 per watt.

So cost of 180 watt panel is = 180 × 160 = Rs. 28, 800.

Total cost of solar panels = 250 × 28800 = Rs. 72, 00000.

2. Cost of 3-φ Inverter: - 36 KVA or 45 KW of an inverter /Power Conditioning Unit is

used; multiply the size of the inverter by Rs. 25 per rated watt.

Cost of inverter = 25 × 45,000 = Rs. 11, 25,000.

3. Cost of 3-φ step up Transformer: - 36 KVA or 45 KW of a step up transformer is used;

multiply the size of the transformer by Rs. 20 per rated watt.

Cost of transformer = 20 × 45000 = Rs. 9, 00000.

4. Cost of battery bank: - Exide Invared 400 Tubular Inverter Battery 12 V, 150Ah Price –

8,400/- . 40 numbers of batteries in two strings of 20 batteries in each string are used. [34]

So, cost of battery bank = 40 × 8400 = Rs 3, 36, 000.

Subtotal: Rs. 95, 61, 000.

5. Multiply the subtotal above by 0.2 (20%) to cover balance of system costs (wire, fuses,

switches, etc.).

Cost Estimate for Balance of System: (9561000 × 0.2) Rs. 19, 12, 200.

Total Estimated PV System Cost is Rs. 1, 14, 73, 200.

6. ANNUAL ENERGY GENERATION

The annual energy generation from the SPV power plant has been worked out based on the

data on mean global solar radiant exposure over Haryana at district Kaithal. The mean global

solar radiant exposure varies from 2.53 kWh/m² /day in the month of December to 6.24 kWh/

m²/day in the month of April according to HARSAC and from 3.36 kWh/m² /day in the

month of December to 6.4 kWh/m²/day in the month of May according to NASA. The

month-wise mean global solar radiant exposure is given at table below.

Table 8 Mean Global Solar Radiant Exposure Kaithal, HARYANA (Acc. To HARSAC)



Month Daily solar insolation in (kWh/m²/day) Energy Generated(kWh)

Jan 2.76 4894

Feb 4.15 6646

March 4.86 8617

April 6.24 10707

May 5.86 10390

June 5.04 8648

July 4.6 8156

Aug 4.47 7926

Sept 4.5 7722

Oct 4.85 8600

Nov 3.42 5868

Dec. 2.53 4486

Monthly Average 4.44 7619

Table 9 Mean Global Solar Radiant Exposure Kaithal, HARYANA (Acc. To NASA)

Month Daily solar insolation in (kWh/m²/day) Energy Generated(kWh)

Jan 3.58 6348

Feb 4.38 7015

March 5.59 9912

April 6.1 10467

May 6.4 11348

June 6.2 10639

July 5.5 9752

Aug 5.14 9114

Sept 5.23 8974

Oct 4.71 8351

Nov 4.01 6881

Dec. 3.36 5957

Monthly Average 5.02 8614

Month Wise load calculation of HCTM, Campus based upon assumptions:

Table 10 Month wise load assumption



Month Type of load Load (KW) % of Total load

(45 KW)

Jan Lighting+ computer 18 40

Feb Lighting+ computer 18 40

March Lighting+ computer + fan load 27 60

April Lighting+ computer + fan load 38 85

May Lighting+ computer + fan load 38 85

June Lighting+ computer + fan load 12 25

July Lighting+ computer + fan load 12 25

Aug Lighting+ computer + fan load 40 90

Sept Lighting+ computer + fan load 40 90

Oct Lighting+ computer + fan load 40 90

Nov Lighting+ computer 16 35

Dec. Lighting+ computer 16 35

Table 11 Month wise load and energy generation (according to HARSAC)

Month Energy consumption(KWh) Energy generated(KWh) Energy

surplus

(KWh)

Jan 3348 4894 1546

Feb 3024 6646 3622

March 5022 8617 3595

April 6840 10707 3867

May 7068 10390 3322

June 2160 8648 6488

July 2232 8156 5924

Aug 7440 7926 486

Sept 7200 7722 522

Oct 7440 8600 1160

Nov 2880 5868 2988

Dec. 2976 4486 1510



Table 12 Month wise load and energy generation (according to NASA)

Month Energy consumption(KWh) Energy generated(KWh) Energy

surplus

(KWh)

Jan 3348 6348 3000

Feb 3024 7015 3991

March 5022 9912 4890

April 6840 10467 3627

May 7068 11348 4280

June 2160 10639 8479

July 2232 9752 7520

Aug 7440 9114 1674

Sept 7200 8974 1774

Oct 7440 8351 911

Nov 2880 6881 4001

Dec. 2976 5957 2981

7. SIMPLE PAYBACK ANALYSIS:

A simplified form of cost/benefit analysis is the simple payback technique. In this method,

the total first cost of the system is divided by the first-year energy cost savings produced by

the system. This method yields the number of years required for the system to pay for itself.

For new construction, it can be used to evaluate conventional construction to energy-efficient

design alternatives. In simple payback analysis, we are assuming that the service life of the

energy efficiency measure will equal or exceed the simple payback time. Simple payback

analysis provides a relatively easy way to examine the overall costs and savings potentials for



a variety of project alternatives. While the payback period analysis does not take into

consideration the time dependent value of money, nor the total accumulated cost or savings

over the life of the system, for systems with equal expected lives, simple payback period can

be applied to determine relative performance among alternatives.

Simple Payback time (years) = Total cost of the system/ Annual Savings

Energy Consumption data

The energy consumption data from year 2010 -11 of HCTM, campus provided by accounts

office, HCTM was used for this study and is shown in Table 13

Table 13 Energy Consumption data of HCTM, campus

S.No. Month Total Units

Consumed

Utility Rate inclusive all charges

(Rs./KWh)

Total

Electricity

Bill (Rs.)

1 Jan 50385 4.6 2,31,771

2 Feb 52290 4.6 2,40,534

3 March 59500 4.67 2,78,234

4 April 94500 4.76 4,49,820

5 May 139250 4.68 6,52,554

6 June 155250 5.64 8,76,620

7 July 124250 6.06 7,53,220

8 Aug 136250 6.06 8,25,675

9 Sep 105045 4.93 5,18,670

10 Oct 93885 4.56 4,28,163

11 Nov 62465 4.6 2,87,339

12 Dec 53150 4.6 2,44,490

Graph for Monthly Variations in electricity bill of HCTM, Kaithal



Graph 2

Simple Pay Back Time the total savings are given below.

Table 14 – Savings for different months (According to HARSAC)

S.No. Month Total Units produced with

PV


(Rs./KWh)

Savings

(Rs.)

1 Jan 4894 4.6 22,512

2 Feb 6646 4.6 30,571

3 March 8617 4.67 40,241

4 April 10707 4.76 50,965

5 May 10390 4.68 48,625

6 June 8648 5.64 48,774

7 July 8156 6.06 49,425

8 Aug 7926 6.06 48,031

9 Sep 7722 4.93 38,069

10 Oct 8600 4.56 39,216

11 Nov 5868 4.6 26,992

12 Dec 4486 4.6 20,635

Annual Savings = Rs. 4, 64,056.

Simple payback time = Total cost of system / Annual savings

= 1, 14, 73, 200/ 4, 64, 056

= 24.7 years (According to HARSAC)

0

1,000,000

Jan

Feb

March

April

May

June

July

Aug

Sept

Oct

Nov

Dec.

Bill in

Rs.

monthly variation in electricity bill of HCTM, Kaithal



Table 15 – Savings for different months (According to NASA)

S.No. Month Total Units produced with

PV


(Rs./KWh)

Savings

(Rs.)

1 Jan 6348 4.6 29,200

2 Feb 7015 4.6 32,269

3 March 9912 4.67 46,289

4 April 10467 4.76 49,822

5 May 11348 4.68 53,108

6 June 10639 5.64 60,003

7 July 9752 6.06 59,097

8 Aug 9114 6.06 55,230

9 Sep 8974 4.93 44,241

10 Oct 8351 4.56 38,080

11 Nov 6881 4.6 31,652

12 Dec 5957 4.6 27,402

Annual Savings = Rs. 5, 26, 393.

Simple payback time = Total cost of system / Annual savings

= 1, 14, 73,200/ 5, 26, 393 = 21.7 years (According to NASA)

8. CONCLUSION

The methodology adopted seems satisfactory for determining the possible plant capacity for

an arbitrarily chosen area. The design described is based on the potential measured. System

sizing and specifications are provided based on the design made. Finally, cost analysis is

carried out for the proposed design. Total Estimated 45 KW PV System Cost is Rs. 1, 14,

73,200. Annual energy generation is also calculated. From calculations done in chapter 6, it is

clear that the estimated energy generated per month from block A is more than the energy

requirement. This surplus energy generated can be stored and supplied to the hostels or

.residential blocks in the campus during night time or may be used when sun is not available

or can be sold to grid. . In the end of chapter 6, the simple payback period is calculated

according to the solar radiation data given by two agencies namely HARSAC and NASA and

found to be 24.7 years and 21.7 years respectively. From the results, it can be concluded that

at current utility rate and demand charges, the system is not economically feasible. However,



in future, at higher utility rates like Rs 10-12/Kwhr and rebates from the government or

utility, the system may be cost effective. With rebates, the demand for the PV panels will rise

gradually leading to more production of panels and a likely drop in price thereby making the

system more cost- effective.

FUTURE SCOPE

In future we will calculate the number of PV arrays and cost of the system which can meet

the load demand of all campus. In starting we have not taken into account the air-conditioners

load. In future we will include the load of air-conditioners. A detailed Cost analysis can be

conducted considering carbon credit to show whether it is economically viable or not. Since

the performance of PV system is strongly dependent on loss factors such as shading, PCS

losses, mismatch, PV array temperature rise, etc. There is a necessity for reviewing these loss

factors to evaluate and analyze accurately the performance of PV system. This system can be

designed with also some another electrical appliances like DC- DC booster for boosting up

the voltage wherever is necessary, filter for suppressing the ripples etc. Another transformer

less design also can be done. DC –DC choppers with variable duty cycle can be used along

with filters. For direct application of DC that kind of system can be designed. Intelligent

devices like microprocessors, PLC (programmable logic controller) may be added to the

system to keep the operating point (maximum power point) for maximum efficiency. To

taken care of the uncertainty in the insolation level, use of fuzzy control can be done. Use of

feedback path for automatic control-position control servo for changing the transformation

ratio of variac can be used. A detailed performance analysis of the present system can be

carried out to show its reliability as a future work. Solar PV is a technology that offers a

solution for a number of problems associated with fossil fuels. It is clean decentralized,

indigenous and does not need continuous import of a resource. On top of that, India has

among the highest solar irradiance in the world which makes Solar PV all the more attractive

for India. The state of Orissa and Andhra Pradesh also houses some of the best quality

reserves of silica. India has a large number of cells and modules manufacturers. In spite of all

above advantages Indian Photo Voltaic programme is still in the infancy stage. One of the

reasons could be absence of simple, action oriented and aggressive PV policy of the country

both in the state and central level. More quickly we do it with the professionals more we

protect our future energy security.

REFERENCES



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on the Output Power” IEEE 8th international conference on electronics measurement and

instruments, pp. 1-278 - 1-282, 2007.

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[25] [http: Photovoltaic modules] ―Photovoltaic modules, system and application available

at www.icpress.co.uk/etextbook/p139/p139_chap15.pdf



FUNDS MANAGEMENT OF ICICI BANK

Manju Sharma*

ABSTRACT

“The ICICI total business Rs. 52000 crores, it is a gigantic Financial Institution. At

present the total business is 1.91 lakh crore. The total deposits are Rs. 202017 crores

total a advances Rs. 181206, net profit for the year Rs. 1006 crores, Net Interest income

Rs. 2035 crores on 31 March 2010.”

Total Assets are worth Rs. 363400 crores, operating profits are worth Rs. 9732 crore,

interest income Rs. 25707 crores. In this paper, I am trying to analyze the the funds

management of ICICI bank.

Keywords: Credit, Demat, Funds, Management, Trade.

* Research Scholar, Singhania University



ANALYSIS OF ICICI FUNDS MANAGEMENT:

The huge funds available with ICICI Bank following functional activities are taken care

are as:

MAIN SERVICES

The following are the main services:

Credit Services

Home Loan Services

Trade Services

Agricultural Services

International Banking Services

Vestro Accounts Services

Proxy Banking Services

OTHER SERVICES

The following are the others services:

Security Market Services

Corporate and Structural Services

Investment Services

Cash Management Services

Foreign Exchange Services

Demat Securities

Credit Services

Abn Amro Bank, Allahabad Bank, American Express Bank, Andhra Bank, Bank of India,

Canara Bank, Central Bank of India, Citibank, Corporation Bank, HDFC Bank, HSBC

Bank, ICICI Bank, Indian Overseas Bank, Oriental Bank of Commerce, Punjab National



Bank, State Bank of India (SBI), Standard Chartered Bank, IDBI, United Bank of India,

UTI Bank.

The advancement of technology and the birth of competition, banks are in the race of

becoming the best in the country. With an eye upon customer satisfaction policy they are

providing best of the best services with the minimum hazards.

Banks like ABN AMRO introduced banking with a coffee. It made a tie-up with one of

the best coffee bar in the country, Barista and remained open till late evening for

customers with a setup of a coffee bar in the premises.

Few banks have introduced world ATM card to make travelers across the globe more safe

and secure. What else. Internet and Phone Banking is the call of the day for banks.

In this race towards the best, selected top 20 banks in the country from all segment it is

not the ranking of banks but only for general information about the top banks in India.

(I) CREDIT SERVICES

ICICI Banks offer a varied range of cards to suit your requirements. These cards having

a wide acceptance, nationally and internationally, coupled with benefits of channels like

Internet and Mobile, with enhance your experiences.

ICICI Bank Credit Cards give you the facility of cash, convenience and a range of

benefits, anywhere in the world. These benefits range from life time free cards, Insurance

Benefits, global emergency assistance service, discounts, utility payments, travel

discounts and much more.

The ICICI Bank Debit Card is a revolutionary form of cash that allows customers to

access their bank account round the clock, around the world. The ICICI Bank Debit Card

can be used for shopping at more than 100,000 merchants in India and 13 million

merchants worldwide.

Presenting ICICI Bank Travel Card. The Hassle Free way to Travel the world. Traveling

with US Dollar, Euro, Pound Sterling or Swiss Francs; Looking for security and

convenience; take ICICI Bank Travel Card. Issued in duplicate. Offers the Pin based

security. Has the convenience of usage of Credit or Debit card.



II) HOME LOANS – SERVICES

The ICICI Bank Home Loans are available in the following cities:

* Aurangabad * Delhi

* Ahmedabad * Mumbai

* Bangalore * Nasik

* Baroda * Nagpur

* Chennai * Pune

* Calcutta

Loan Amount:

The loan amount is up to a maximum of 85% of the value of the property to be financed.

Minimum Amount : Rs. 1 lakh

Maximum Amount : Rs. 10 million

Tenor

The tenor of a ICICI Bank home loan ranges from a period of 1 year to 30 years

depending on the type of loan availed.

Eligibility

The eligibility criteria are:

The applicant should be at least 25 years of age and a maximum of 65 years at

the time of loan maturity.

The applicant should have a regular source of income.

Documentation:

The documents required are:

Passport size photograph of all the applicants.

Residence and age verification, which may be established from the Pan Card,

Election ID, Passport, Driving License or Ration Card

Bank statements for the last six months

Latest salary slip/ statement showing all deductions in case of employed

applicants



Certified copies of Balance Sheets and Profit and Loss accounts, IT

acknowledgments, advance tax challans (for company/ firm and personal

account) for the last three years in case of self-employed applicants.

Memorandum /Articles of Associations for Companies, partnership deeds for

firms and a brief profile of your company/ firm in case of self-employed

applicants.

Property Documents (as and where applicable):

Application form duly filled and signed.

Draft sale agreement

Previous sale agreements

NOC to mortgage from society/ builder as per our format?

Society Share Certificates

Occupancy certificate (Ready property or U/C property)

Original stamped receipts for the payments already made to the builder/ seller,

till date

371 Clearance from the appropriate Income Tax authorities, if applicable.

List of additional amenities from builder where applicable.

Interest Rate Structure

Tenure (years) Interest Rate

1-5 11.25%

6-20 12.75%

21-30 12.85%

EMI Chart per Rs. 1,00,000

Tenor Interest:

11.25%

Interest:

12.75%

Interest:

12.85%

5 years Rs. 2269 N.A. N.A.

20 Years N.A. Rs.1168 N.A.

30 Years N.A. N.A. Rs. 1100

Note: of cause these rates are subject to change with the ordinance of RBI.



Other Costs

Fees: 1.8% of the sanctioned Loan amount.

Processing fee: Rs. 500 (at the time of application)

III) TRADE SERVICES

ICICI Bank offers a wide range of Trade Services designed to assist you in building on

your strengths, so that your company can seize business opportunities across the world.

ICICI Bank has in place a Centralized Trade Services Unit, which adheres to six sigma

standards. As a result, ICICI Bank customers experience fewer delays in receiving

payment, require less effort in locating collecting information, gain increased control

over foreign receivables and experience improved cash flows.

Online Trade Services:

ICICI Bank customers can effect remittances as well as get their applications for issuance

of Letters of Credit and Bank Guarantees processed online. This not only extends

tremendous convenience to the entire process, but also allows the customer to enjoy the

benefits of simplified documentation, online verification of status and savings in cost and

time. Online Trade Services can be availed by enrolling for Corporate Internet Banking

(CIB) offered by ICICI Bank.

Online LC Online EPC

Online Bank Guarantee Online Remittances

Online EEFC

Track the status of your export and import bills, view details of your LCs, guarantees and

forward contracts, get your export LC electronically advised – do all this and more

through our web services.

Advisory Services:



Banks believe in delivering value. ICICI Bank clients can avail our advisory services on

forex markets, currency movements, regulatory issues, risk management and other issues

in trade finance.

Exchange Rates

Track the latest movements in currency to plan your business.

Customized Solutions and New Product Development

ICICI Bank constantly customizes solutions and introduces innovative products for its

Trade Services clients.

Export Document Tracking:

Bank realizes the criticality of time in your trade transaction process. You can now track

the status of shipment of your export documents online.

Arrange for Export Credit Insurance:

Export credit insurance is an important aspect of international trade. Know more about

the services of India’s leading export credit agencies ICICI Lombard and ECGC.

Trade Regulation & Policy Update:

The global trade scenario is governed by country specific as well as international

regulation. Refer to the existing regulations and update yourself with the latest.

Trade Facilitation

In a developing country like India, a number of organizations occupy the role of trade

facilitators. They are a source of valuable information, resources, services and guidance

to Indian exporters.

Country Scan

The economic and political climate of a country influences business decisions of exporter

sand importers across the globe. Coface country reports and country ratings aid you in

taking informed decisions.

Concepts in International Trade:

Global trade transactions are complex. The exporter and importer entering a contract is

only the beginning of a chain of events that need to be precisely coordinated. At one level

it involves document preparation, at another level it requires coordinating with third

party.



IV) AGRICULTURE SERVICES

Adopting innovative approach to Agriculture Business financing and by offering

complete supply chain solutions. ICICI Bank has changed the face/ dynamics of

Agriculture Business Finance in the country.

ICICI Bank, India’s first universal bank, has the financial strength and the expertise to

offer probably the widest array of financial services for your business.

Whatever your requirements, if you are into agriculture business, out dedicated tam of

agriculture sector specialists and finance professionals with deep understanding of the

sectoral business environment will device custom solutions and offer complete supply

chain solutions for your business.

Whether you are in the business of Diary, Sugar, Plantations, Seed sector, Fertilizer

Sector, Infrastructure, Markfeds or Food Processing, ICICI Bank is the one stop shop for

all your financial needs.

V) INTERNATIONAL BANKING SERVICES…

ICICI Bank’s International Banking Division Offers a complete range of correspondent

banking services to banks and financial institutions. The products offered are as under:

Automated INR Payment Services

VOSTRO Accounts

Cross Border Trade Services

Trust and Retention Account Services

INR Agency Clearing Services

Automated INR Payment Services:



This product offers efficient distribution of inward remittance from exchange Houses and

Banks abroad.

Key features of this service are:-

Web/SWIFT messaging facility

Routing of payment through our internal electric network if the account is with

any of our branches.

If accounts are with other banks, distribution is achieved through bank drafts/

cheques by courier.

Cover funding through INR account/or through foreign currency accounts

On-line access to INR account if maintained

MT 950/940 facility

Dedicated helpdesk for backup and tracking

Convenience in funding/ providing cover

Evolving a structure that best address the concerns of all institutions involved in

financing of the project/ other financial requirements. Key features of the product are:

Waterfall management of cash flows

Acting as paying and receiving agent

Foreign Exchange agent

Safekeeping and Custody for the underlying

Account administration

Cash escrows and security escrows

Pre constructions and post construction management of cash flows

Investment services

Regulatory liaison

Advisory Services

Electronic reporting via the Internet or specialist on-line system; Customized MIS

reporting.

INR Agency Clearing Services:

ICICI Bank offers Clearing Services across all major centers for facilitating clearing of

their customer cheques. Key features of the product are:

Clearing of customer cheques through our code as a sub member



Facility to issue demand drafts payable across all our branches by your branch/

branches

Collection of cheques/ instruments through our network

Funds transfer services from other centers to your branch/ branches through our

networks

Customized MIS and a dedicated helpdesk.

VI) VOSTRO ACCOUNTS SERVICE

VOSTRO accounts provide INR account services to correspondent banks. All the

accounts are held in a special center located in our Nariman Point branch at Mumbai. Key

features of the product are:

Access to our network spread across all major centers

Internet access to account

Web based messaging facility/ SWIFT based

Customized MIS

Funding convenience

Competitive tariff

Cross Border Trade Services:

ICICI Bank offers full range of cross border trade services to its correspondent banks.

This services is available across all major destinations in India with significant foreign

trade potential. We have fully integrated communication channels amongst branches,

which directly helps in saving valuable time facilitating cross border transactions.

Advising and confirming of documentary letters of credit

Confirmation/ reissuance of standby LCs and guarantees.

Documentary collections/ open account transactions

Payment processing and distribution

Advising and confirming of documentary credits

Negotiation of documents

Computerized processing ensuring speedy services

Trust and Retention Account Services:



ICICI Bank is one of the leading Trust and Retention (Escrow) Account services

providers in India, have a considerable experience in managing various types of Trust and

Retention accounts including.

VII) PROXY BANKING SERVICES

Indian villages were miles away from mutual funds, insurance and even equity trading.

Thanks to Internet Kiosk and the ATM duo which had made it possible for rural India.

This kiosk has been set up by ICICI Bank in partnership with network n-Logue

Communications in remote villages of Southern part of the country. This is known as

Proxy Banking. With the help of fibre optic cables, this works on wireless in local loop

technology.

Reasons for Setting up of Proxy Banking

58% of rural households still do not have bank accounts.

Only 21% of rural households have access to credit from a formal source.

70% of marginal farmers do not have deposit account.

87% households have no formal credit.

Only 1% rural households rely on a loan from a financial intermediary. The loans

take between 24 to 33 weeks to get sanctioned.

Consumer bribe officials to get loans approved which varies between 10 and 20

percent of the loan amount.

Branch including in rural is a loss-making.

Others Services;

To name a few as:

Security Market Services Corporate and Structural Services

Investment Services Cash Management Services

Foreign Exchange Services Demat Securities

Credit Services



BIBLIOGRAPHY

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publications.1998.



www.gjmr.org

77

EMERGING TRENDS IN HUMAN RESOURCE MANAGEMENT—

A CHALLENGE TO THE ITES

Raunak Narayan*

ABSTRACT

Today’s euphoric corporate environment has posed daunting challenges for human resource

management. While demand for manpower is rising, supply is not able to keep pace. While wage

bills are bloating, quality of manpower is deteriorating. And while, there is a surfeit of

graduates, their employability is low, due to poor skills. This is just the ideal setting for the

management to shed its decades of inhibition take centre stage and dictate strategy alongside

other key functions such as finance, marketing and sales.

Human resource management (HRM) is a process of bringing people and organizations together

so that the goals of each other are met. Over the years, highly skilled and knowledge based jobs

are increasing while low skilled jobs are decreasing. This calls for future skill mapping through

proper HRM initiatives. Globalization of the world economy and several other trends are again

triggering changes in how companies manage and utilize their human resources.

The Indian Information Technology Enabled Services (ITes) industry has been one of the great

success stories of modern India. An industry that did not exist two decades ago is now the bread

and butter of the nation and the envy to the world. It has created international benchmark for

quality, proving to the world and to ourselves that Indian companies can compete globally and

win on quality. It has demonstrated what can be achieved by unleashing the power of middle

class, first generation entrepreneurship in India.

Hence, The ITes organizations which is working on the principle of attracting, managing,

nurturing and retaining their employees is moving ahead with the competition and is having

competitive advantage over other organizations. And to adopt this principle, now it has become

very essential to face the challenges posed by the new trends of HR. It is this theme upon which

this paper has been worked out.



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Keywords—Human Resource Management, Information Technology Enabled Services (ITes),

Competitive Advantage, Attrition, BPO

INTRODUCTION

In the life of any nation, company or individual, movement is life and stagnation is death.

Therefore, as long as companies are growing, they are fully alive. Organizations must move

continuously from one process to another, from one strategy to another, and from one structure

to another. So long as we are renewing these kinds of things and re-looking at them, that’s where

growth and achievement comes in. Human Resource Management (HRM) has evolved

considerably over the past century, and experiences a major transformation in form and function

primarily within the past two decades. Driven by a number of significant internal and external

environmental forces, HRM has progressed from a largely maintenance function, to what many

scholars and practitioners today regard as the source of sustained competitive advantage for

organizations operating in a global economy. Human Resource (HR) is the only function where

building capabilities takes place—building capabilities of organization and individuals. And that

is why HR will have to build organizations whether it is ITes or any other. Building,

grooming/preparing people, building different kind of mindsets, defining roles and making them

understand what kind of society and landscape is going to emerge, become extremely important.

ITes is defined as outsourcing of processes that can be enabled with information technology and

covers diverse areas like finance, HR, administration, health care, telecommunication,

manufacturing, etc. Armed with technology and manpower, these services are provided from e-

enabled locations. ITes is a catchall term used for the myriad processes that ant bureaucratic

entity undertakes in servicing its employees, vendors, customers. The Indian Ites industry has

rapidly opened up, expanded, matured and with a wave of consolidation has scripted new

initiatives.

*University of Calcutta



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With substantial evolution being witnessed, India has become the ideal and most preferred

offshore destination. Numerous factors such as supply of skilled manpower, global standard

telecom infrastructure, proactive and positive policy environment and friendly corporate tax

policies have given India an edge in the global marketplace. In spite of offering distinct

advantages such as cost competitiveness, highly skilled labor and a high level of service

maturity, the industry witnessed certain unique challenges especially in the area of HR. Of

myriad HR-related challenges faced by the industry, the critical ones are the attrition and scarcity

of professionals equipped with necessary domain knowledge and communication skills. Despite

being global phenomena, these challenges have become a matter of concern in Indian ITes

industry.

EMERGING TRENDS IN HR

Over the years, highly skilled and knowledge based jobs are increasing while low skilled jobs are

decreasing. This calls for future skill mapping through proper HRM initiatives. Indian

organizations are also witnessing a change in systems, management cultures and philosophy due

to the global alignment of Indian organizations. Hence, it is necessary for the management to

invest considerable time and amount, to learn the changing scenario of the HR in the 21st

century. In order to survive the competition and be in the race, HR department should

consciously update itself with the transformation in HR and be aware of the HR issues cropping

up. With high attrition rates, poaching strategies of competitors, there is a huge shortage of

skilled employees and hence, a company’s HR activities play a vital role in combating this crisis.

Suitable HR policies that would lead to the achievement of the organization as well as the

individual’s goals should be formulated.

Some recent trends that are being observed are as follows:

Traditional HR Practice Emerging HR practice

Administrative Role Strategic Role

Reactive Proactive



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Separate from Company Mission Key part of Organizational Mission

Production Focus Service Focus

Functional Organization Process based Organization

People as expenses People as key Investments/ Assets

To leapfrog ahead of competition in this world of uncertainty, organizations have introduced six-

sigma practices. Six-sigma uses rigorous analytical tools with leadership from the top and

develops a method for sustainable improvement. These practices improve organizational values

and helps in creating defect free products or services at minimum costs.

Human resource outsourcing is a new accession that makes a traditional HR

department redundant in an organization

With the increase of global job mobility, recruiting competent people is also

increasingly becoming difficult, especially in India. Therefore, organizations are

required to work out a retention strategy for the existing skilled manpower.

To have a competitive advantage over rivals, organizations are working on the

principle of Attracting, Managing, Nurturing and Retaining their employees.

Companies no more believe in the tall hierarchical structures, and cubical with

closed doors of the boss, but have given way for flat organizational structures

with more spans of control and less chain of command. In place of being the

autocratic leader or manager, they play the role of team builders, mentors, coach,

or counselors.

Following the principles of retaining the brains in the organization, the policies

have become more and more flexible providing alternative and flexible work

schedule. Flexi time, compressed week, job sharing, etc

Organizations today are not only making the structure and policies employee

friendly rather they are trying to improve the quality of work life where



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employees can enjoy their working and will be able to manage the balance

between work life and personal life. They provide them the in-house facility of

health club, yoga, meditation, alternative work schedule, picnics, and family get

together where they can reduce their stress and strains. They also provide

educational and medical facility.

Training and Development are the other areas where organizations are trying to

take the lead over other organizations so that employees can be made multi-

skilled to handle multiple tasks. The new horizon has opened up where the

organizations competing are clubbing together to form the network of talents.

Other areas where remarkable changes are being made are in communication

pattern. Gone are those days when employees feared talking to their bosses.

Things are replaced by cross communication, gang plank mechanism, open door

policy, internet, intranet, mentoring, counseling, coaching, etc. Communication is

no more restricted to form top to bottom rather bottom to up is encouraged more

in the organization to make functioning more smooth and to have grievance free,

satisfied employees.

With the continuous rise in competition, business cannot flourish if individualism

is prevailing in the organization. Therefore, to meet the need of the time the

growing organizations are following collectivism culture, where working in

groups and teams are emphasized.

Performance appraisal has also taken a new shape. It is not confined to the boss

and subordinates, rather more emphasis is being given on overall appraisal of the

employees (360 degree appraisal). Employees are also given opportunities for

succession growth.

The ITes industry, which is rapidly growing industry in India, is not an exclusive of the above

stated emerging trends; moreover it is mainly the cause and effected industry for the changes in

HRM. Hence, it is very essential to know the challenges posed by those merging HR trends to

ITes industry.



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CHALLENGES OF EMERGING HR TRENDS TO ITES

Attracting and Retaining Talent—

The ITes industry has, during the last decade, been probably the most attractive sector to work

in. It has therefore been able to get nest talent. The challenge now is to safeguard and build on

this prime position. Attractive compensation, challenging assignments, good working conditions

and growth opportunities are amongst the main determinants of where talent gravitates, along

with the indefinable “glamour value” of a company. Taking care of these parameters is a

necessary task for the ITes industry.

High level of Attrition

While India does have a large talent pool, not all are ‘industry –ready’ or equipped with the

necessary skill sets to become useful to the companies. This means there is plenty of supply at

the entry level but huge gaps in the middle and senior management levels. This has resulted in

increased levels of poaching and attrition cases. Presently, the average attrition rate faced by this

industry is somewhere around 30-35 percent.

Not a serious career option

Another very critical issue of concern for HR managers is that most students and professionals

working in call centers do not see this industry as a long-term career option due to the inherent

nature of the job (monotonous and lacking challenges), most of the time there is low interest in

the work.

Mismatch of Expectations

Expectations mismatch leads to higher attrition. This is partly due to the perceptions created in

the general public with respect to the career growth, type of work, compensation offered,

competition, etc. Many a times, people are not able to create a work-life balance and often opt

out. The right positioning will help attract the right profile of associates , which will



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automatically manage their expectations from the industry and this will, in turn lead to lower

attrition rates.

Communication Issue

Lack of effective communication is another contentious issue. The absence of regular, two-way

communication between agents, their team managers and the senior management is a common

complaint in the industry.

High training costs

On an average, the ITes companies incur three types of training costs—voice/ accent, soft skills

and process training. For a start-up, in the initial stage the training costs will be high. It generally

accounts for four months salary of employee hired, though the actual training would be probably

being for just a month.

Generating motivation and increasing efficiency

Generating motivation and increasing efficiency is far more difficult in situations where the job

is repetitive and routine, as in many ITes operations. This is a real challenge to managers. This is

important because a key part of India’s value proposition as the outsourcing destination is based

on productivity and quality- factors that depend critically on motivation.

Compensation

Compensation is probably the single most important parameter in most cases. The challenge here

is to provide an attractive package in context of rising expectations, and yet minimize overall

cost escalation. In this situation, “poaching” people from other companies by offering higher pay

packages is self-defeating for the industry as a whole. An important correction lies in ensuring an

ever-growing and sufficiently large supply pipeline for fresh entrants.

The challenges of workplace diversity

The future success of any organization relies on the ability to manage a diverse body of talent

that can bring innovative ideas, perspectives and views to their work. The challenge faced of

workplace diversity can be turned into a strategic organizational asset if an organization is able



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to capitalize on this melting pot of diverse talents. With the mixture of talents of diverse cultural

backgrounds, genders, ages, and lifestyles, an organization can respond to business opportunities

more rapidly and creatively, especially in the global arena, which must be one of the important

organizational goals to be attained. More importantly, if the organizational environment does not

support diversity broadly, one risks losing talent to competitors.

Dearth of innovative and efficient HR professional

AIMA 2003 report projected that tourism and IT/ ITes would generate between 20- 72 million

jobs by 2020. Most of this employment-generation is happening in people-intensive sectors.

Thus, the need for a strong HR backbone arises. Even at a very conservative estimate we are

looking at least 5 million new jobs in the next five years. And a quick calculation would show

that even if we need one HR professional for 1000 employees, one needs at least 5000 new HR

professionals

Few Solutions

Moving towards ‘B class’ cities

Due to the high demand and supply gap and scaling attrition numbers, many companies are

moving towards ‘B class’ cities like Chandigarh, Bhopal, Lucknow and Dehradun, to attract

talent and set up their operations. In Karnataka, the ITes companies are looking towards

Mangalore, Hubli, and Mysore rather than concentrating only in Bangalore.

Looking for career oriented employees—there is also a change in employee profile, with

organizations looking for older and experienced people who will bring in stability. The

requirement is for those people for whom salary is not just a pocket money, but a career

opportunity. The ideal employees for BPOs would be people from the middle and lower-middle

income households, who are willing to work hard and have a strong sense of responsibility and

dedication towards their employers. Initially, though it might lead to scaling training costs, as the

section might lack in basic communication and soft skills.

Proper rewarding

A research report says that in today’s scenario.



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70% of your employees are less motivated than they used to be

80% of your employees could perform significantly better if they wanted to

50% of your employees only put enough effort into their work to keep their job

One might be aware of Employee reward covers how people are rewarded on accordance with

their value to an organization. The ways in which people are valued can make a considerable

impact on the effectiveness of the organization, and is at the heart of the employment

relationship.

Educating about career opportunities

The common misconception is that there are only three position in ITes or BPOs-that of an

agent, a team leader and the project leader. There is however more to it. According to Deepak

Dhawan, VP (HR) of EXL Services, there is an immense opportunity for professionals with a

CA or MBA background: “An individual can choose from managing quality, get into training,

Sex sigma process, problem solving equations, relationship management, HR and workflow

activities or business development”.

Government initiatives

Nasscom has recently started a project with different private players training institutes and

academia in Andhra Pradesh, Karnataka and Kerala, for preparing “employable” ITes workforce.

According to A. Sundararajan, IT secretary of Kerala, “It will help chart out indicative domain-

wise manpower requirement projections from the industry. Skill set standardization, Government

recognized certification in ITes, and inclusion of ITes as a discipline in graduate studies by

universities will help in making ITes as a career choice by students”.

Creating effectiveness and efficiency through motivation

Empowering, engaging and energizing employees are established ways of creating effectiveness

and efficiency through motivation. Organizational structures, systems and procedures are

facilitators of these, and companies need to focus greater attention on these aspects.

Providing an excellent physical work environment



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The ITes industry has to provide an excellent physical work environment. It needs to continue to

be a leader in providing these facilities, including food, fitness and sports facilities. While these

“add-ons” are not inconsequential, work satisfaction through challenging, cutting-edge

assignments, and substantial growth prospects are definitely major determinants for retention.

Consider the employees as a resource

The statement “people are our greatest asset”, though a cliché that is often heard in corporate

boardrooms is, nevertheless, true in most industries. However, nowhere are human resources as

critically important as in the ITes sector. Human resources are not only the drivers and principal

value-creators of the output of this industry; they are also the intellectual capital or the

“infrastructure investment”.

HR managers should evolve with new roles

With the increase in competition, locally or globally, organizations must become more adaptable,

resilient, agile and customer-focused to succeed. And within this change in environment, the HR

professional has to evolve to become a strategic partner, an employee sponsor or advocate,

change mentor within the organization. The HR manager will also promote and fight for values,

ethics, beliefs, and spirituality within the organizations.

Improving employability

Despite the large number of students graduating, it is common to hear companies complain about

not finding suitable candidates. The updating of syllabi and ensuring relevant content would be

useful. In addition, it would be worthwhile to include some basic IT courses for the Science,

Mathematics, and Commerce and Economics students. This would enable graduates in these

streams to be considered for employment in a number of ITes jobs.

CONCLUSION

To conclude, change is necessary to survive. Those who change with the change survive and

those don’t vanish. What is today may be obsolete tomorrow. It is necessary to upgrade and

restructure every time to withstand and face the situations. HR policies of the ITes organization

should also be changed with the time and new strategies, policies should come up to retain the



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talents in the organization to increase the success ratio in today’s competitive global

environment. HR managers have to manage all the challenges that they would face from

recruiting employees, training them, and developing strategies for retaining them and building up

an effective career management system for them. Just taking care of employees would not be

enough; new HR initiatives should also focus on the quality needs, customer-orientation,

productivity, stress, team work and leadership building.

REFERENCES

[1] Dr. Nagaraju Battu (2007), “Human Resource Development”

[2] Dr. Pritam Singh- HR, The Taskmaster, Times of India daily Ascent, 24th November, 2010

[3] Prof. Anitha H.S. “Succession Planning”, “Benchmarking for Infusing Competitive Culture

among Indian PSUs” and “Commercial viability of PSUs”, Deccan Herald, August 25,2009

[4] Mrs. Soumya K.R. (2010) “Assessment of training need and evaluation of training

effectiveness on employees of select ITes in Bangalore”

[5] Dr. Alvin Chan (2010), “Challenges of HRM”

[6] Rituparna Banerjee (2010), “Emerging trends on HRM”

[7] Punita Jasrotia Phukan (2009), “Changing HR paradigm in the ITes sector”

[8] K.P. Kanchana (2009), “Emerging trends in HR”

[9] Sanjeev Sharma, “Retention Strategies in ITes-BPO industry”

[10] www.bpoindia.org



FUNDAMENTAL CHALLENGES IN EMERGENT FIELD OF SENSOR

NETWORK SECURITY AND INITIAL APPROACHES TO SOLVE THEM

D. P. Mishra*

M. K. Kowar **

ABSTRACT

Rapid technological growth in the area of micro electro-mechanical systems (MEMS) has

spurred the development of small inexpensive sensors capable of intelligent sensing. A

significant amount of research has been done in the area of connecting large numbers of these

sensors to create robust and scalable Wireless Sensor Networks (WSNs). Proposed applications

for WSNs include habitat monitoring, battlefield surveillance, and security systems. Although

individual sensor nodes have limited capabilities, WSNs aim to be energy efficient, self-

organizing, scalable, and robust. Almost all of the research is centered on meeting these

challenges, but relatively little work has been done on security issues related to sensor networks.

The resource scarcity, ad-hoc deployment, and immense scale of WSNs make secure

communication a challenging problem. Since the primary consideration for sensor networks is

energy efficiency, security schemes must balance their security features against the

communication and computational overhead. Paper will describe the fundamental challenges in

the emergent field of sensor network security and the initial approaches to solve them.

Keywords: Security, Sensor Networks

*Department of Computer Science & Engineering, BIT, Durg

** Department of Electronics & Telecommunication Engineering, BIT, Durg



INTRODUCTION & MOTIVATION

Rapid technological growth in the areas of micro electro-mechanical systems and miniaturization

has spurred the development of a new kind of network. This network is composed of small,

inexpensive sensors capable of intelligent sensing. Much research has been done with the aim of

connecting large numbers of these sensors to create robust and scalable Wireless Sensor

Networks (WSNs) on the order of hundreds of thousands of devices. Communication usually

consists of source nodes which sense the data and return it to sink nodes over multiple hops.

Sink nodes may be ordinary sensor nodes or specialized base stations with greater resources.

Sensor network proponents envision a future in which thousands to millions of tiny sensor

devices will be embedded in almost every aspect of life. The goal is to create intelligent

environments capable of collecting massive amounts of information, recognizing significant

events automatically, and responding appropriately. Sensor networks facilitate “large-scale, real-

time data processing in complex environments” [14]. If sensor networks are to attain their

potential, however, secure communication techniques must be developed in order to protect the

system and its users. The need for security in military applications is obvious, but even more

benign uses, such as home health monitoring, require confidentiality so widespread deployment

and overall success of sensor networks will be directly related to their security strength.

SENSOR SECURITY CHALLENGES

The nature of large, ad-hoc, wireless sensor networks presents significant challenges in designing

security schemes. Some of the most pronounced challenges are described below.

Wireless Medium

The pervasive applications proposed for sensor networks necessitate wireless communication

links. Furthermore, the ad-hoc deployment of sensor motes makes wired communication

completely inappropriate. The wireless medium is inherently less secure because its broadcast

nature makes eavesdropping simple. Any transmission can easily be intercepted, altered, or

replayed by an adversary. The wireless medium allows an attacker to easily intercept valid

packets and easily inject malicious ones.



Ad-Hoc Deployment

The ad-hoc nature of sensor networks means no structure can be statically defined beforehand.

The network topology is always subject to changes due to node failure, addition, or mobility.

Nodes may be deployed by air drop, so nothing is known of the topology prior to deployment.

Since nodes may fail or be replaced the network must support self-configuration. Security

schemes must be able to operate within this dynamic environment.

Hostile Environment

Most challenging factor is the hostile environment in which sensor nodes function. Motes face

the possibility of destruction or (perhaps worse) capture by attackers. Since nodes may be in a

hostile environment, attackers can easily gain physical access to the devices. Attackers may

capture a node, physically disassemble it, and extract from it valuable information (e.g.

cryptographic keys). The highly hostile environment represents a serious challenge for security

researchers.

Resource Scarcity

The extreme resource limitations of sensor devices pose considerable challenges to resource-

hungry security mechanisms. A representative example of a sensor device is the Mica mote. It

has a 4 MHz Atmel ATMEGA103 CPU with 128 KB of instruction memory, 4 KB of RAM for

data, and 512 KB of flash memory [7]. The radio operates at up to 40 Kbps bandwidth at a range

of a few dozen meters. Such hardware constraints necessitate extremely efficient security

algorithms in terms of bandwidth, computational complexity, and memory.

Immense Scale

Finally, the proposed scale of sensor networks poses a significant challenge for security

mechanisms. Simply networking tens to hundreds of thousands of nodes has proven to be a

substantial task. Security mechanisms must be scalable to very large networks while maintaining

high computation and communication efficiency.

ATTACKS & DEFENSES



Security goals for sensor networks include the same four primary objectives as conventional

networks: availability, confidentiality, integrity, and authentication. Although sensor network

security is characterized by the same properties as traditional network security. Karlof and

Wagner identify two major classes of attackers: mote-class and laptop-class. Mote-class attackers

are constrained to the CPU, power, bandwidth, and range limitations of the mote platform.

Laptop-class attackers, however, may possess more powerful hardware such as a faster CPU, a

larger battery, a high-power radio transmitter, or a sensitive antenna. This section examines the

security attacks and corresponding defenses at each level of the network.

Physical Layer

Attacks at the physical level include radio signal jamming and tampering with physical devices.

Jamming- well-known attack on wireless communication is simply interference with the radio

frequencies used by a device’s transceiver. It represents an attack on the availability of a

network, thus creating a denial-of-service condition [14].

The standard defense against jamming involves the use of spread-spectrum or frequency hopping

techniques. Prevention of denial of service attacks is a difficult task. Since most sensor networks

currently use single frequency communication, Wood, Stankovic, and Son have proposed a

Jammed Area Mapping (JAM) service which emphasizes detection and adaptation in response to

jamming. They assume that only a portion of the network is being jammed and attempt to map

this area so it can be avoided. Nodes in the affected area switch to low power mode. Information

about jammed areas is passed to the network layer so it can successfully route packets around the

dead areas. If spread spectrum techniques cannot be incorporated into motes, then detection

algorithms such as JAM may be important in defending against jamming attacks.

Tampering A second problematic issue at the physical layer is the relative ease and potential

harm of device tampering. This problem is exacerbated by the large-scale, ad-hoc, pervasive

nature of sensor networks. Access to thousands of nodes spread over several kilometers cannot

be completely controlled [14]. Attackers may very well have greater physical access to nodes

than the network administrator. Nodes may be captured, interrogated, and compromised without



difficulty. While node destruction is undesirable, node compromise may be even more dangerous

because of the cryptographic material compromised.

Link Layer

The link and media access control (MAC) layer handles neighbor-to-neighbor communication

and channel arbitration. Like the physical layer, the link layer is particularly susceptible to denial

of service attacks.

Collision If an adversary can generate a collision of even part of a transmission, he can disrupt

the entire packet [Perrig, Stankovic, and Wagner 2004]. A single bit error will cause a CRC

mismatch and possibly require retransmission. In some MAC protocols, a corrupted ACK may

cause exponential back-off and unnecessarily increase latency. Although error-correcting codes

protect against some level of packet corruption, intentional corruption can occur at levels which

are beyond the encoding scheme’s ability to correct. The advantage, to the adversary, of this

MAC level jamming over physical layer jamming is that much less energy is required to achieve

the same effect: preventing devices from successfully transmitting packets.

Exhaustion Another malicious goal is the exhaustion of a network’s battery power [10]. In

addition to the previous types of attacks, exhaustion may also be induced by an interrogation

attack. In the IEEE 802.11-based protocols, for example, Request To Send (RTS) and Clear To

Send (CTS) packets are used to reserve bandwidth before data transmission. A compromised

node could repeatedly send RTS packets in order to elicit CTS packets from a targeted neighbor,

eventually consuming the battery power of both nodes [10].

Unfairness A more subtle goal of the previously described attacks may be unfairness in the

MAC layer [10]. A compromised node can be altered to intermittently attack the network in

such a way that induces unfairness in the priorities for granting medium access. This weak form

of denial of service might, for example, increase latency so that real-time protocols miss their

deadlines [10].

Network Layer



The network layer is responsible for routing packets across multiple nodes. Due to the ad-hoc

nature of sensor networks, every node must assume routing responsibilities. WSNs are

particularly vulnerable to routing attacks because every node is essentially a router.

Classifications of routing attacks are summarized below and are followed by a general discussion

of secure routing techniques.

False Routing Information The most direct attack on routing is to spoof, alter, or replay routing

information. This false information may allow adversaries to create routing loops, attract or repel

traffic, shorten or extend route lengths, increase latency, and even partition the network

[7].Clearly, the falsification of routing information can cripple a network. The standard solution

is to require authentication for routing information,

Selective Forwarding Selective forwarding is a more subtle attack in which some packets are

correctly forwarded but others are silently and intentionally dropped. A compromised node could

be configured to drop all packets, creating a so-called black hole. Since the network is capable of

handling node failure it may conclude that the compromised node has failed and find another

route. If the compromised node selectively forwards packets, the neighboring nodes will believe

that the malicious node is still functioning correctly and continue to route packets to the node.

Sinkhole Attack In the sinkhole attack, a node spuriously advertises a very good route to a sink

node (base station) in order to lure all nearby traffic to itself. Thus all traffic within some sphere

of influence is drawn into the sinkhole centered at the compromised node. This attack enables the

selective forwarding attack along with other attacks. An adversary mounting a laptop-class attack

may actually provide the fastest route to a sink by using its greater range to reach the sink in a

single hop.

Sybil Attack The Sybil attack occurs when a single node claims to be other nodes in the network.

Geographic routing protocols are particularly vulnerable to the Sybil attack since they are

designed with the assumption that no node can be in two places at once. If a node lies about it

location, it can significantly disrupt routing performance in geographic routing protocols.



Wormhole Attack The wormhole attack is used to convince two possibly distant nodes that they

are neighbors so that the attacker can place himself on the route between them. Basically, the

adversary tunnels messages from one part of the network to another through an out-of-bound

channel available only to the attacker. Wormholes typically involve two colluding nodes.

HELLO Flood Attack The Hello flood attack, a novel attack proposed by Karlof and Wagner,

exploits routing protocols that require periodic HELLO packets be transmitted to announce the

presence of a node. Nodes which receive a HELLO packet assume they are within radio range of

the sender, i.e., the sender is a neighboring node. This assumption may be false in the case of a

laptop-class attacker. An adversary with a powerful transmitter may be able to transmit a single

HELLO packet to every node in the network and convince every node that it is a one-hop

neighbor. As a result, the network is left in a state of confusion. If, for example, the attacker

advertises a very quick route to a base station in the HELLO packet, many non-neighbor nodes

will attempt to route packets through the malicious node. In actuality, however, they will be

sending packets into oblivion. Karlof and Wagner point out that this attack is actually a “one-

way, broadcast wormhole.” The simplest solution for this attack is to verify the bidirectionality

of a link before acting on its information. Essentially, routing messages from one-way links are

ignored. Karlof and Wagner propose an identity verification protocol to defend against the

HELLO flood attack.

Acknowledgement Spoofing The last routing attack Karlof and Wagner identify is the

acknowledgement spoofing attack. Several routing protocols rely on link layer

acknowledgements for determining next-hop reliability. If an adversary can respond for weak or

dead nodes, he can deceive the sender about the strength of the link and effectively mount a

selective forwarding attack. The artificial reinforcement allows the attacker to manipulate the

routing through the weak or dead node.

There have been several approaches to defend against network layer attacks. Authentication and

encryption are a first step, but more proactive techniques such as monitoring, probing, and



transmitting redundant packets have also been suggested. Secure routing methods protect against

some of previous attacks. Proposed techniques are described below.

Authentication & Encryption Link layer authentication and encryption protect against most

outsider attacks on a sensor network routing protocol. Even a simple scheme which uses a

globally shared key will prevent unauthorized nodes from joining the topology of the network. In

addition to preventing selective forwarding and sinkhole attacks, authentication and encryption

also make the Sybil attack impossible because nodes will not accept even one identity from the

malicious node [7]. SPINS and TinySec are two proposed solutions for link level encryption and

authentication.

Monitoring A more active strategy for secure routing is for nodes to monitor their neighbors and

watch for suspicious behavior [14]. In this approach, nodes act as “watchdogs” to monitor the

next hop transmission of the packet.

Probing Another proactive defense against malicious routers is probing [14]. This method

periodically sends probing packets across the network to detect blackout regions. Since

geographic routing protocols have knowledge of the physical topology of the network, probing is

especially well-suited to their use.

Redundancy is another strategy for secure routing [14]. An inelegant approach, redundancy

simply transmits a packet multiple times over different routes. Hopefully, at least one route is

uncompromised and will correctly deliver the message to the destination.

PROPOSED SOLUTIONS

While the majority of the research in sensor networks has focused on making them feasible and

useful, a few researchers have proposed solutions to the security issues discussed previously.

Sensor network security mechanisms can be divided into two categories: communication

protocols and key management architectures. Communication protocols deal with the



cryptographic algorithms used to achieve availability, confidentiality, integrity, and

authentication. Key management architectures handle the complexities of creating and

distributing keys used by communication protocols.

Communication Protocols

Currently there have been two major secure communication protocols proposed for sensor

networks: SPINS [2] and TinySec [Karlof, Sastry, and Wagner 2004]. Both protocols work at the

link level to provide message confidentiality, authentication, and integrity using symmetric

cryptography. The limited memory and CPU speeds of sensor nodes almost completely exclude

the use of asymmetric cryptography sensor networks.

SPINS SPINS (Security Protocols for Sensor Networks) is comprised of two link layer

protocols: SNEP and µTELSA. SNEP (Secure Network Encryption Protocol) provides data

confidentiality, two-party authentication, and data freshness. Perrig et al. identify three patterns

of communication in sensor networks: node to base station, base station to node, and base station

to all nodes. SNEP handles the first two types, and µTELSA handles the last. In order to

minimize computation and memory requirements, SNEP bases all symmetric cryptographic

primitives (encryption, message authentication code, hash, and random number generator) on the

same block cipher, RC5. Another design goal is to minimize communication overhead. This is

accomplished by reducing the packet overhead to 8 bytes and by storing state information instead

of transmitting it with each packet.

SNEP supports data authentication, replay protection, and semantic security [11]. Authentication

is provided by calculating and appending a message authentication code (MAC) to each

message. A MAC is essentially a cryptographically secure checksum [Karlof, Sastry, and

Wagner 2004]. The MAC is recalculated upon reception and compared to the value in the

transmission. To implement replay protection, SNEP requires a synchronized counter value at

each node. The MAC is calculated using a secret key and the counter. As a result, out-of-sync

packets will not be accepted. SPINS includes a counter exchange protocol for synchronizing

counter values between two hosts. Although maintaining a synchronized counter adds significant



overhead, it allows semantic security, a strong security property which assures that identical

messages are encrypted differently each time they are encrypted. For example, if a sensor is

simply reporting YES or NO regarding the occurrence of some event, an attacker may be able to

discover the encrypted value of NO and subsequently be able to understand all encrypted

transmissions. By encrypting the data based on the counter as well as the key, each NO will

encrypt differently.

μTELSA, the second part of SPINS, provides authenticated broadcast for sensor networks. The

goal of μTELSA is to allow base stations to transmit authenticated broadcasts to all of the nodes

while preventing a compromised node from forging messages from the sender. μTELSA uses

symmetric mechanisms to create an asymmetric system using a loosely synchronized clock.

Receivers buffer broadcast packets until they receive the decryption key which is disclosed once

in a specified time interval (epoch). The keys are calculated using a one-way hash function (F)

and are disclosed in the reverse order that they are generated. Once a node receives a key, it can

apply the same hash function to calculate the keys for previous epochs and decrypt buffered

packets. Figure 1 illustrates this process.

Figure 1: μTELSA key disclosure and

computation. Each hash mark denotes an

epoch. P1, P2,…P7 represent packets.

SPINS performs reasonably well according to its authors. Although key setup is expensive (4

ms), encrypting a 16 byte message and calculating its MAC only takes 2.5 ms. The limited

bandwidth of the test platform, 10 kbps, allows time to perform key setup, encryption, and MAC

calculation for every packet. The performance of μTELSA is bounded by the amount of buffer

space available. Consequently, key disclosures must happen relatively frequently and must be

reliably received.

The stated limitations of SPINS are that it does not completely deal with compromised nodes and

it does not deal with denial-of-service attacks. SPINS merely ensures that a comprised node

does not reveal the key to every node in the network. Additionally, SNEP needs tight

synchronization of counters since they are not transmitted. Another design weakness is the



dependence of μTELSA on buffering packets. The extremely limited storage space characteristic

of sensors devices makes buffering particularly unattractive.

TinySec TinySec is a more recent solution to the sensor link layer security problem. The

TinySec protocol provides access control, message integrity, and message confidentiality.

TinySec explicitly omits replay protection, recommending it be performed at the application

layer. The designers of the protocol emphasized usability and transparency in hopes of increasing

TinySec’s adoption. To this end, TinySec has been incorporated into the official release of

TinyOS, the small, event-driven operating system designed for sensor motes. Unlike SPINS,

TinySec has been fully implemented and exhibits promising performance. Encryption and

authentication can be performed in software with only 10% energy overhead and 8% increased

latency.

TinySec operates in two modes: authenticated encryption (TinySec-AE) and authentication only

(TinySec-Auth). Like SPINS, TinySec implements authentication and integrity by the use of

message authentication codes (MACs). TinySec uses a cipher block chaining construction (CBC-

MAC) for computing and verifying MACS because of its efficiency and speed. TinySec’s

designers make authentication mandatory but encryption optional because not all messages need

to be kept secret. Message authentication and integrity, both provided by the MAC, are critical

for security since they block invalid senders and protect the data from corruption. The MAC

protects the entire contents of the packet, including header information. Since the 2 byte CRC of

a normal TinyOS packet is redundant, it is replaced by a 4 byte MAC.

Figure:2

AM (1)

Len (1)

Src (2)

Ctr (2)

Data (0 - 29)

MAC (4)

Dest (2)

AM (1)

Len (1)

Data (0 - 29)

MAC (4)

Dest (2)

IV

AM (1)

Len (1)

Data (0 - 29)

MAC (4)

Dest (2)

Grp (1)

(a) Tiny-Sec AE Packet Format

(b) Tiny-Sec Authentication Packet Format

(c) Tiny-OS Packet Format



Figure 2: TinyOS and TinySec packet formats. The byte size of each field is indicated. Hatched

fields are protected by the MAC. In TinySec-AE, the dark grey data portion is encrypted.

This effectively adds only 2 bytes of overhead for authentication. Refer to Figure 2(b) for an

illustration of the TinySec-Auth packet format.

If confidentiality of message contents is required by the application, TinySec-AE is used. For

encryption, TinySec uses the Skipjack block cipher by default but also supports RC5. In order to

provide semantic security, TinySec uses an initialization vector (IV) to encrypt each packet and

sends this value in each packet. To minimize packet size overhead, the entire header contents

(destination, AM, length, and source) and a 2 byte counter are used as the IV. This effectively

gives an 8 byte IV for the cost of only 2 bytes. Figure 2(c) illustrates this structure. Sufficiently

long IVs are critical because repeated IVs leak information about a cryptosystem. In the case of

the CBC cipher used by TinySec, only the length of the longest shared prefix of two messages is

revealed if the entire 8 byte IV repeats. A repetition only occurs when one node sends two

packets to the same destination with the same AM type, length, and counter value. Given the low

data rate for sensor nodes, the probability for such a repetition is low.

The performance of TinySec has proven that sensor network security can be efficiently done in

software. TinySec requires 728 bytes of RAM and 7146 bytes of program space. The energy

overhead imposed by TinySec is 3% for TinySec-Auth and 10% for TinySec-AE. The extra

computation increases the time to transmit a packet 1.6% for TinySec-Auth and 7.9% for

TinySec-AE. The energy, bandwidth, and latency of TinySec are all less than 10% and due

almost entirely to the increased packet length. Not surprisingly, TinySec is being used by several

other research projects throughout the country. With its impressive performance and ease of use,

TinySec is the best sensor network security communication protocol to date.

Key Management Architectures

Despite TinySec’s merits as a communication protocol, it does not even attempt to solve the

issue of key management. Key management handles the generation and secure distribution of

cryptographic keys as well as techniques to protect the network from lost keys. A variety of



strategies exist for accomplishing this task. Some of the major approaches are summarized

below.

LEAP The efficiency and speed of symmetric algorithms are well suited to sensor nodes and

have been the default choice for sensor network designers. Most symmetric schemes require keys

be loaded onto devices before deployment. Using a different key for every link provides the best

security against compromised nodes but is incompatible with the basic nature of sensor

networks. Sensor networks rely on data aggregation and in-network processing to increase

network efficiency. Nodes along the path consolidate data to reduce the overall number of

messages in the network. This cannot take place if messages are encrypted. In an effort to

balance these two extremes, LEAP [14] utilizes four types of keys for different security levels.

LEAP supports an individual key shared only with the base station, a pairwise key shared with

another sensor node, a cluster key shared with multiple neighboring nodes, and a group key

shared by all the nodes in the network. The advantage of LEAP is that it supports in-network

processing while minimizing the security impact of a compromised node to the node’s

immediate neighbors. LEAP provides a key for every need. This property offers convenience at

the cost of storage space and complexity, neither of which are abundantly available to sensor

nodes.

LKHW Another approach to key management is to use a hierarchy to store keys. Pietro et al.

propose a scheme based on Logical Key Hierarchy (LKH) built on top of directed diffusion.

Directed diffusion is a data-centric routing protocol that uses exploratory flooding to find the

best path to send events of interest. The extension of LKH over directed diffusion comprises the

LKH Wireless (LKHW) protocol. LKHW is a secure multicast scheme that enforces backward

and forward secrecy. New nodes cannot decrypt old traffic, and evicted nodes cannot decrypt

future traffic. LKHW uses a tree structure to store keys. The root of the tree serves as the key

distribution center (KDC), and each leaf represents a user. Each leaf stores the set of keys

belonging to its direct ancestors up to the KDC. The reason for using a tree structure is to

increase the efficiency of re-keying. Re-keying occurs whenever a node joins or leaves the



group. The energy required for re-keying is shown to be approximately logarithmic to the group

size.

Random Key Predistribution Another novel approach to key management is random key

predistribution [2]. In this strategy, a random pool of keys from the key space is preloaded into

each node. Two nodes must find a common key in their sets in order to communicate. A

challenge-response protocol is used to verify that two nodes have a key in common.

TinyPK Despite the fact that asymmetric cryptography has been almost universally considered

to be too resource-intensive for use in sensor networks, there have been some efforts to adapt

public cryptography techniques to sensor devices. TinyPK [13] is one such project that uses the

RSA cryptosystem to handle symmetric key distribution. To minimize calculations by the sensor

motes, e=3 is used as the public exponent. Encryption simply requires cubing a 1024-bit number

and taking its residue modulo a large prime number. Implementing a public-key system requires

a modest amount of infrastructure including a Certificate Authority (CA). The CA’s public key is

preloaded onto each node and is used to verify messages from the CA. Despite the adaptations,

TinyPK still performs slowly by current standards. Table 1 summarizes the operation times for

RSA encryption at various key sizes.

RSA Key Size Time (sec)

512 3.8

768 8.0

1024 14.5

Table 1: RSA encryption (exponentiation) times

Watro et al. confess that the current implementation is too slow for RSA private operations

(decryption) since execution times would be on the order of tens of minutes. They suggest using

TinyPK as a method of authenticating external parties to the sensor network and moving the

computationally expensive operations to the external device when possible. Although public key

cryptography possesses many advantages in handling key management, it is currently infeasible



for node-to-node communication in sensor networks. Perhaps asymmetric techniques will be

viable on more powerful hardware of the future. Most researchers predict, however, that devices

will ride Moore’s Law down the price curve instead of increasing in speed. If this is the case,

then algorithmic optimizations will be required for public-key systems.

CONCLUSION

Sensor networks hold the potential to transform the way computing affects life. In order to reach

this potential, secure communication must be achieved. The wireless, ad-hoc, resource-limited

nature of sensor networks creates substantial challenges for researchers. At the physical layer,

probable attacks include frequency jamming and device tampering, two techniques with known

solutions but entailing greater financial cost. The link layer of sensor networks is also susceptible

to denial of service attacks in the form of maliciously induced collisions and exhaustion attacks.

The network layer is particularly vulnerable since every node in a sensor network is a router.

Although link layer encryption and authentication serve as a first layer of defense, maximum

security can only be achieved by designing routing algorithms with security in mind. SPINS and

TinySec satisfactorily address the issue of link layer encryption, authentication, and integrity but

require key management architectures to be practical. Current key management solutions are not

sufficiently adapted to the unique requirements of sensor networks. If sensor networks are to

reach their potential, secure communication must exist.

REFERENCES

[1] Agrawal, Dharma P.; Qing-An Zeng. 2003. Introduction to Wireless and Mobile Systems.

Brooks/Cole – Thompson, Pacific Grove, CA.

[2] Chan, H., A. Perrig, and D. Song. Random Key Predistribution Schemes for Sensor

Networks. IEEE Symposium on Security and Privacy (SP) (May 11 - 14, 2003).

[3] Hill, Jason, Robert Szewczyk, Alec Woo, Seth Hollar, David Culler, and Kristofer Pister.

System architecture directions for networked sensors. In Proceedings of the Ninth

International Conference on Architectural Support for Programming Languages and

Operating Systems (ASPLOS IX) (November 2000).



[4] Hu, Y.C., A. Perrig, and D.B. Johnson. Rushing Attacks and Defense in Wireless Ad Hoc

Network Routing Protocols. Proceedings of the ACM Workshop on Wireless Security

(WiSe'03) (San Diego, California, September 19, 2003).

[5] Huang, Q., J. Cukier, H. Kobayashi, B. Liu, and J. Zhang. Fast Authenticated Key

Establishment Protocols for Self-Organizing Sensor Networks. Proceedings of the

Workshop on Wireless Sensor Networks and Applications, (WSNA'03) (San Diego,

California, September 19, 2003).

[6] Jolly, G., M.C. Kuscu, P. Kokate, and M. Younis. A Low-Energy Key Management

Protocol for Wireless Sensor Networks. IEEE Symposium on Computers and

Communications (ISCC'03). (Kemer – Antalya, Turkey, June 30 - July 3 2003).

[7] Karlof C. and D. Wagner. Secure Routing in Wireless Sensor Networks: Attacks and

Countermeasures. Proceedings of the First IEEE International Workshop on Sensor

Network Protocols and Applications (SNPA'03) (11 May 2003).

[8] Karlof, Chris, Naveen Sastry, and David Wagner. TinySec: A Link Layer Security

Architecture for Wireless Sensor Networks. Proceedings of the Second ACM Conference

on Embedded Networked Sensor Systems (SenSys’04) (November 3 - 5, 2004).

[9] Law, Y. W., S. Dulman, S. Etalle, and P. Havinga. Assessing Security-Critical Energy-

Efficient Sensor Networks. 18th IFIP TC11 Int. Conf. on Information Security, Security

and Privacy in the Age of Uncertainty (SEC) (Athens, Greece, May 2003).

[10] Perrig, Adrian, John Stankovic, and David Wagner. Security in Wireless Sensor

Networks. Communications of the ACM, Volume 47, Issue 6 (June 2004): 53-57.

[11] Perrig, Adrian, Robert Szewczyk, Victor Wen, David Culler, and J.D. Tygar. SPINS:

Security protocols for sensor networks. In The Seventh Annual International Conference

on Mobile Computing and Networking (MobiCom 2001), (2001).

[12] Pietro, R.D., L.V. Mancini, Y.W. Law, S. Etalle, and P. Havinga. LKHW: A Directed

Diffusion-Based Secure Multicast Scheme for Wireless Sensor Networks. International

Conference on Parallel Processing Workshops (ICPPW'03) (Kaohsiung, Taiwan. October

6 - 9, 2003).

[13] Warto, Ronald, Derrick Kong Sue-fen Cuti, Charles Gardiner, Charles Lynn, and Peter

Kruus. TinyPK: Securing Sensor Networks with Public Key Technology.



[14] Wood, A.D. and J.A. Stankovic. Denial of Service in Sensor Networks. IEEE Computer,

Volume: 35, Issue: 10 (Oct. 2002):48-56.

[15] Wood, A.D., J.A. Stankovic, and S.H. Son. JAM: A Jammed-Area Mapping Service for

Sensor Networks. In The 24th IEEE International Real-Time Systems Symposium (RTSS)

(Cancun, Mexico, December 2003).



THE ECONOMICS & BUSINESS OF EUROPEAN LEAGUE FOOTBALL

Dr. Rosy Kalra*

ABSTRACT

Football is the most popular sport in the world & certainly one of the most lucrative businesses.

It remains unparalleled in generating emotion & passion across the planet irrespective of the

divide & differences separating people. Furthermore, Football is a surprisingly resilient industry

& not only weathered the storm of the global financial crisis that crippled major European

economies, but emerged unscathed & stronger from it all. Just a look into the latest revenue

figures amongst the richest European League clubs confirms this belief as their combined

revenue has for the first time exceeded the €4 billion mark with almost all the clubs managing to

improve upon their last years performance.

Key Terminology: Amortization -The annual cost of writing down the cost of buying new

players

*Assistant Professor, Amity Business School, Amity University, Noida (UP).



INTRODUCTION

Amongst a seemingly positive ambit, there lies great churning not only in the operation of the

Football clubs but also the governing regulations. The major concern stem from the almost

precipitous levels of debt prevailing amongst the richest, most successful & popular European

League clubs. 56% of the 733 clubs that had an audit done by UEFA (Union of European

Football Associations) suffered a loss. In the English Premier League alone 14 of the 20 clubs

made a loss in their most recent accounts.

But what is more worrying is that debt levels continue to increase at an alarming rate & shows no

sign of abating. As Football clubs continue to grow more & more indebted serious question are

being leveled at the sustainability of the various business models prevalent amongst European

Football Clubs.

The above developments subsequently are of major significance to one of the most popular &

lucrative football leagues in Europe – The English Premier League. The success & consistent

presence of English clubs in the latter stages of the elite European competitions display the

importance of top tier English Football clubs & therefore how the top English Football clubs

adapt to the changing landscape has deep ramifications in the evolution of the European

Footballing landscape in the long run.

LITERATURE REVIEW

The review of literature was carried to explore the ways & techniques that could be used to better

understand & interpret the Football industry & its true economic reality. The review of literature

facilitated comparison of the results of previous analysis & the results of this study. Hence,

review of literature has been instrumental in giving a better meaning to this study & has been a

source of guidance for carrying out this study. Some of them include-

Babatunde Buraimo and Rob Simmons (2006) model the impacts of market size and team

competition for fan base on matchday attendance in the English Premier League over the period

1997-2004 using a large panel data set. It constructs a comprehensive set of control variables and

use tobit estimation to overcome the problems caused by sell-out crowds. It also accounts for

unobserved influences on attendance by means of random effects attached to home teams. Also



treatment of market size, with its use of Geographical Information System techniques, is more

sophisticated than in previous attendance demand studies.

The European Club Footballing Landscape report by UEFA (2008) is an 80-page report

published in four languages – English, French, German and Russian – and the analyses

contained within have formed an important basis for recent discussions on financial fair play, as

well as contributing to increased transparency in club football – one of UEFA's key club

licensing objectives. The report also deals with non-financial areas such as competition

structures and attendance trends and, for the first time, features a pan-European analysis of

stadium ownership and licensing results.

The Bundesliga’s report on “The Economic State of Professional Football” The DFL released

report detailing the economic state of professional football in Germany & includes the financial

results that had previously been part of the DFL’s Bundesliga Report. The release presents the

particulars of increased revenue & increased equity in the German league but also points to the

subsequent increase in the prevailing debt levels inspite of strong performances in the elite

European competitions translating to higher prize money payouts.

Deloitte’s Annual Review of Football Finance describes a comparative survey of revenue

among European clubs through its annual editions of Deloitte’s Football Money League. It

details its finding through a football “Rich List”, ranking the top 20 European clubs on the basis

of their financial clout & turnover. The Football Money league profiles the highest earning

clubs in the world’s most popular sport & is considered the most contemporary and reliable

analysis of clubs’ relative financial performance. There are a number of methods that can be

used to determine clubs’ relative size – including measures of fan base, attendance, broadcast

audience, or on-pitch success. However, the Money League focuses on the clubs themselves,

comparing revenue from day to day football operations which we believe is the best publicly

available financial comparison.




Type of Research:

Analytical research uses facts and information already available, and analyzes these to make a

critical evaluation of the material. This study is an analytical research carried out to critically

examine the functioning of Elite European League Football with a focus towards top English

Football clubs & to study the viability of the various prevalent economic models existing within

the Football industry. For the analysis historical data of past six years (2004-2009) has been

taken spanning the top clubs in England.

Objective(s)

Determine functional sustainability amongst current operating practices of financial

indiscipline in Major football clubs

To evaluate the colossal debt levels prevalent at the top echelons of club football,

To determine the adequacy of legislations governing major clubs.

Data Analysis Method Description

1) Critical analysis of the financials of Football clubs qualifying for UEFA’s elite European

competition spanning England’s Top Tier Football Clubs

2) To analyse the revenue streams & expenditure patterns of major football enterprises

including review of Balance Sheets released by individual clubs wherever applicable.

3) To examine the correlation between transfers spend & player wages contributing towards

financial brinkmanship between clubs.

4) Excerpts of interview & opinions of top football experts including analysis of newspaper

reports & articles by eminent football authors.



DATA ANALYSIS & INTERPRETATION

For any credible analysis of the health of football finances, it is imperative to objectively

examine the biggest & the most lucrative money spinning Football leagues & their domestic

clubs. Therefore the English Premier League which is the world's most watched association

football league & consequently the world's most lucrative football league in terms of revenue,

with combined club revenues of over £2 billion in 2008–09 exceeding that of Spain's La Liga

and Germany's Bundesliga , form the crux of the focus in examining the status of Football’s

financial Landscape.

ARSENAL Football Club

Arsenals financial results for the year ended 31 May 2010, have been nothing short of record

breaking with revenue of £380 million (Year 2009 £313 million) and profit before tax of £56

million (Year 2009 £46 million).Another notable figure was that of Profit Before Tax which was

up 23%, from previous year’s profit of £35 million.

But the most impressive element was that this enabled the club to repay £130 million of bank

loans, thereby reducing the net debt to £136 million from just under £300 million. So any further



sales on the property front will generate surplus cash as the property business is now essentially

debt-free. This is especially credit worthy given the downturn in the property market arising out

of recession.

Table 1: Arsenal- Profit Growth

Arsenal has earned significant property revenue - £157 million from £88 million previously as

displayed in Table 1. But this was also marked by a subsequent growth in expenses as well, so

the profit from property only increased marginally from £6 million to £11 million. But clearly,

the £45 million football profit still drives the business. There is also some hefty gains that can be

now anticipated generating surplus cash from property sales.



Given the healthy numbers, operating profit for the football business actually fell by a third (£10

million) to £20 million from £30 million. Also there was a small decrease in revenues by £2

million attributed to the economic downturn & fewer home games. But at the same time, higher

wages also increased expenses by £8 million. Fortunately, the football operating profit of £45

million pre-tax profit (including player sales) more than made up for the rise in expenses.

.In the last three years alone, Arsenal have produced combined pre-tax profits of £138 million –

an astonishing figure in the world of football.Arsenal’s profit growth has been largely driven by

impressive revenue growth which has ballooned to £223 million from £115 million, almost

double in the last 5 years consequently placing Arsenal 5th in the last year’s Deloittes Money

League.

Arsenal’s revenue growth is a consequence of moving into their new stadium & not television

unlike the vast majority of other clubs in the English league. Gate receipts doubled to £90

million from £44 million, reflected in the steep change in revenue figures from the year 2007

after moving into Ashburton Grove. The £20 million “mortgage” is now easily serviced from

additional £50 million revenue per season generated as a result of the increased capacity stadium.

Television Broadcast rights has been the biggest revenue driver for all clubs including arsenal. In

2010 alone, Arsenal’s television revenue jumped to £85 million from £73 million, a 15%

increase. Still as a percentage of revenue, the clubs dependence on T.V Broadcast revenue is

relatively small at 38% than compared to other clubs as shown in Table 2



Table 2: Revenue of Premier League 2008/09

One aspect where Arsenal lags behind their competitors, especially the continental European

teams, is in Commercial Revenue. In spite of weak figures in this section which is much lower

than that of other big English clubs, there was actually a decline of £4 million generating a total

of only £44 million.

Arsenal have already moved to address this glaring void with the new CEO Ivan Gazidis

strengthening the clubs commercial team with high profile recruits with an aim to significantly

bolster Commercial revenue while aggressively exploring overseas markets including in the

Middle East, Far East and the USA while expanding retail presence through international brand

building.



On the cost side, reflecting the resigning of many players on long term contracts have resulted in

a rise in wages to £111 million, a jump of 6% .They also include the strengthening of the

executive team, which must come at a price, though theoretically should also increase revenue.

Also as a result of wage increases, the wages to turnover ratio has increased reversing the trend

of the last 3 years although this still remains the runner-up in terms of the best wages to turnover

ratio prevalent in the English League.

Figure 1: Wages vs. Turnover

The entry of the Russian oil tycoon Roman Abramovich through his purchase of Chelsea

Football Club in 2003 heralded a new era in football & its operations where balancing books was



considered no longer an important requirement. As attempts to keep up & compete with Roman

Abramovich’s Chelsea, many clubs followed its method of purchasing success & glory through

wielding the cheque book, often without considering neither the cost nor its consequences.

Remarkably, arsenal in this turbulent period has remained one of the only few clubs to earn a

surplus of £2 million in player transfers... This figure pales in comparison to the huge sums

splashed in the transfer market by other clubs, the likes of Manchester City, Chelsea, Liverpool

and Manchester United. This approach of being averse to spending huge amounts of money by

risking financial collapse & bankruptcy is especially laudable in the context of the free spending

competitors.

Another impressive performance has been in the clubs property venture which subsequently

earned the club a significant £157 million from the sale of apartments as part of the Queensland

redevelopment project undertaken by the club. This deserves special praise as such results were

achieved in the face of one of the worst recessions the world has witness coupled with the

subsequent downturn in the property market which had, at time forced the club into requesting

extension of the deadline for the repayment of the bank loan. This has significantly curtailed &

subsequently eliminated the property debt, enabling the club bring down its gross level of debt to

£263 million. The net debt is significantly lowered to only £136 million if one takes into account

the cash balances of £128 million as shown in Figure 2.

Figure 2: Annual Debt



Chelsea Football Club Limited

The entry of the Russian oil tycoon Roman Abramovich through his purchase of Chelsea

Football Club in 2003 heralded a new era in football & its operations where balancing books was

considered no longer an important requirement. As attempts to keep up & compete with Roman

Abramovich’s Chelsea, many clubs followed its method of purchasing success & glory through

wielding the cheque book, often without considering neither the cost nor its consequences.



A look at Chelsea’s financial accounts reveals few distinct points, the foremost being that the

club held the rather unenviable record for the highest wage bill ever accounted for by a Club in

the English premier League at the time of submission of the Club’s accounts in the year 2009.

This mammoth wage bill & high transfer spending is in stark contrast to the often announced

goal of breaking even as stated by the then CEO of the Club Peter Kenyon.

As displayed in Table 3, Chelsea have incurred continual losses since 2004 with the £44.4m loss

incurred in the 2009..Although the clubs have managed to consistently reduce losses (until 2010

where excess of £70 million in losses were disclosed) it does not detract from the fact that the

deficit was massive in the form of £140 million back in the year 2005. As the clubs management

insist that the losses are on a downward trajectory, Chelsea’s recent foray into the transfer

marker splashing in excess of £70 million on just two players (Fernando Torres & David Luis)

especially after recently announcing massive losses does not augur well for the financial health

of the club.

Table 3: Chelsea Football Club Profit and Loss Account



From the £140 million back in the year 2005, losses have now reduced to £44.4 million, a net

reduction of about £95.6 million. But significantly nearly 80% of this reduction can be attributed

to have come from the transfer market, i.e. £74m with £40.4 million higher profit on account of

player sales notwithstanding lower amortization which is £33.6 million lower & fewer

termination payments. This translates into only £8.7 million of the reduction actually coming

from football operations. In the context of the T.V broadcast bonanza era the results are a

dampener to say the least.



In spite of the Clubs keenness to pat them on the back regarding improvement in cash flows the

net cash outflow from operating activities of £13.1m 2009 is exactly the same as it was in 2004

& still is in the negative.

Another moot point being the revised valuations of the players in the balance sheet, intangible

assets (basically net book value of the players) have decreased from £143.6m to £77.8m by

£65.8m in just twelve months. This is further compounded by the fact that the squad now needs

major replacements & for the club itself the vicious cycle of debts & losses shows no sight of an

end.

Therefore, it is clear that Chelsea need to find ways of reaching the elusive break-even target and

the right way is to increment revenue.. In the long-term it is vital to leverage Brand Chelsea to

increase commercial revenue in a significant way if the club is to progress financially. This

involves exploring sponsorship revenue & stadium naming rights in which Chelsea lags behind

in comparison with the other big four of the league.

Revenue from T.V Broadcasting rights is at a healthy £79.1 million, behind only Manchester

United in the league. In addition to this, like other English football clubs Chelsea too will receive

an additional windfall of funds as a result of the new agreement on overseas rights, translating

into an extra £7.5m per annum for the next three years for the club. There seems to be little

revenue potential left for the club to pursue to achieve its target of breaking even, as a result

Deloittes in their annual football review report quoted, “the club faces a significant challenge to

regain a top five position in our Money League.”

Therefore, it is clear that the club is significantly farther from attaining its stated financial

objectives while struggling to break free from its dependence on its Russian owner. The club at

the very least has to start thinking about the changing footballing landscape & evolve into a

viable business. A good start would be to stop hemorrhaging further losses & significantly

improve bottom lines.

FINDINGS & RECOMMENDATIONS

According to UEFA report 54% of Europe's top-division teams reported operating losses (before

transfers) in the 2008 financial year.



The above analysis of top English clubs provides clear warnings of financial mismanagement &

unsustainability. In addition, it is clear from the above analysis of the top clubs in Europe that

very few manage to generate profits & fewer still can lay claim to have a viable & sustainable

business model. This is a stark indictment of not only the larger governance of the sport where

lackadaisical financial excesses have not only been tolerated but encouraged as also the

questionable conduct of individual football clubs in England & across Europe adopting irrational

financial measures leading themselves to precipitous levels of unsustainable wage inflation &

debt.

Amidst this backdrop of financial excesses & subsequent losses the German Bundesliga is the

flag bearer & role model for the much touted UEFA fair play regulations. The German football

association’s success can be gauged from the fact that no Bundesliga club has ever gone

bankrupt during a running competition or was unable to complete the season. The Bundesliga’s

success in this matter spans 40 years with member clubs operating for years with positive results

& definitely offers approaches that can be adopted elsewhere to restore financial perspective

among the other European footballing heavyweights. It owes its success to a robust licensing

system, exercising rigorous financial control over member clubs where expenditure is strictly

required to be in line with existing revenues thus limiting the possibilities for using incoming

capital to replace revenues.

Spiraling wage inflation is a serious concern affecting football clubs. A salary cap vis-à-vis

Major league baseball would be difficult to implement in the sport of football. Another effective

approach therefore, would be to strictly enforce wage discipline among football clubs by

establishing the maximum limit that the club can spend on player salaries based upon a

percentage of their turnover. This would ensure that if even a club over extends itself financially

while purchasing a player, his wages would have to necessarily come from the revenues

generated by the club. Thus such clubs would have to exercise prudence to see if they can afford

the player’s wages before making a purchase decision in the transfer market.

When one considers the complexity of football when compared to a more traditional business, it

is strange that it is subject to the current “one size fits all” model of legislation. Few other



businesses pay vast fees to secure employees, nor do they pay their employees in a complex

manner that includes basic pay, image rights and performance-related bonuses, and yet no

special demands are made of football clubs to disclose this clearly in their annual financial

statements.

Naturally, this has big implications for financial transparency within the industry. With outside

observers relying on measures such as wages as a percentage of a club’s turnover to gauge a

club’s sustainability, the lack of breakdown of the “wage” mean that one struggles to draw any

reliable conclusions.

CONCLUSION

Even in the game of Football, questions of financial prudence & perspective ultimately seek their

resolution through optimum balance, and the same is true for the economics of sport. The

challenge for the sport is to find a dynamic balance between desire for success and money

necessary to analytically grasp the passionate and pragmatic complexities of the beautiful game.

A strong revolutionary wind is blowing through Europe’s footballing landscape providing a

compelling paradigm shift in how the business of football functions & evolves.

UEFA has produced a club licensing benchmarking report on European club football – the

broadest of its kind ever undertaken – covering financial results from more than 600 top-division

clubs from UEFA's 53 member national associations forming an important basis for recent

discussions on financial fair play, as well as contributing to increased transparency in club

football – one of UEFA's key club licensing objectives.

All in all, it is clear that while many clubs are continuing to operate successfully, there are many

operating less-sustainable strategies. Reports indicate that 54% of Europe's top-division teams

reported operating losses (before transfers) in the 2008 financial year.

While some clubs in every UEFA member association were able to break even, the analyses

identify other signs of financial overstretching and clubs living beyond their current means.

Amid the record Broadcast deals & revenues there are some increasingly clear warning signs.

The many clubs across Europe that continue to operate on a sustainable basis are finding it

increasingly difficult to coexist & compete with clubs that incur losses & transfer fees beyond



their means & reporting losses year after year, without themselves following the same approach

at the same time succumbing to a vicious cycle of debt.

Unless there is a comprehensive overhaul in the way football clubs operate & conduct business,

there is a distinct possibility of grave consequences.

REFERENCES

Rodney Fort and Joel Maxcy, " Competitive Balance in Sports Leagues: An Introduction”

Journal of Sports Economics, (2003)

Babatunde Buraimo and Rob Simmons, “Market size and attendance in English Premier

League Football” The Department of Economics, Lancaster University Management School,

Lancaster LA1 4YX,UK, (2006)

Leit˜ao, Jo˜ao, “The Taylor Effect on the Performances of the Red Devil’s Football Brand”,

University of Beira Interior, (2007)

The Bundesliga’s report on “The Economic State of Professional Football”

The UEFA Club Licensing and Financial Fair Play Regulations Report

http://soccernet.espn.go.com/news/story/_/id/874859/gordon-taylor:-football-facing-

government-intervention?cc=4716

http://www.thesun.co.uk/sol/homepage/sport/football/3392577/Chelseas-wage-bill-is-an-

amazing-172million.html

http://www.telegraph.co.uk/sport/football/competitions/premier-league/8314698/English-

clubs-defy-the-economic-recession-to-retain-elite-status-in-European-money-league.html

http://www.espnstar.com/football/premierleague/news/detail/item581775/Clarke:-Level-of-

football-debt-precipitous/

http://en.wikipedia.org/wiki/Uefa



http://en.wikipedia.org/wiki/UEFA_Champions_League

http://en.wikipedia.org/wiki/FIFA

http://en.wikipedia.org/wiki/Premier_League



AN ALGORITHM FOR SOLVING A CAPACITATED FIXED CHARGE

BI-CRITERION INDEFINITE QUADRATIC TRANSPORTATION

PROBLEM WITH RESTRICTED FLOW

S.R. Arora*

Kavita Gupta**

ABSTRACT

In this paper a capacitated fixed charge bi-criterion indefinite quadratic transportation problem

with restriction on the total flow is studied. An algorithm to find the efficient cost time trade off

pairs in a capacitated fixed charge bi-criterion indefinite quadratic transportation problem with

bounds on rim conditions is developed. The algorithm is developed by forming a related fixed

charge indefinite quadratic transportation problem and it is shown that to each basic feasible

solution called corner feasible solution to related transportation problem, there is a

corresponding feasible solution to this restricted flow problem. It is also shown that the efficient

cost time trades off pairs to the given problem are derivable from this related problem the

algorithm is illustrated with the help of a numerical example.

Keywords: optimum time cost trade off, capacitated transportation problem, fixed charge, bi-

criterion indefinite quadratic transportation problem, restricted flow.

* Ex-Principal, Hans Raj College, University of Delhi, Delhi-110007, India

** Department of Mathematics, Jagan Institute of Management Studies, 3 Institutional Areas,

Sector-5, Rohini, Delhi, India



1. INTRODUCTION

The fixed charge transportation problem was originally formulated by G.B Dantzig and

W.Hirisch [8] in 1954.Thirwani et.al. [9] in 1997 developed an algorithm for finding the time

cost trade off pairs in a fixed charge bi-criterion transportation problem with restricted flow.

Later, Arora et.al [1-2] also studied the indefinite quadratic transportation problem.

Another important class of transportation problem consists of capacitated transportation problem.

If the total flow in a transportation problem with bounds on rim conditions is also specified, the

resulting problem makes the transportation problem more realistic. Moreover, if the total

capacity of each route is also specified then optimal solution of such problems is of greater

importance which gives rise to a capacitated transportation problem. Many researchers like A.K

Bit et.al. [6], K.Dahiya et.al. [7] Have contributed in this field.

In 1976, Bhatia et .al. [5] provided the time cost trade off pairs in a linear transportation

problem. Then in 1994, Basu et.al. [4] Developed an algorithm for the optimum time cost trade

off pairs in a fixed charge linear transportation problem giving same priority to cost as well as

time. Arora et.al. [3] Studied time cost trade off pairs in an indefinite quadratic transportation

problem with restricted flow.

In this paper, a capacitated fixed charge indefinite quadratic transportation problem with bounds

on rim conditions giving same priority to cost and time is studied along with restriction on the

total flow. An algorithm to identify the efficient cost time trade off pairs for the problem is

developed.

2. PROBLEM FORMULATION

Linear functions are widely used in modeling a mathematical optimization problem. Also

quadratic functions and quadratic problems are the least difficult to handle out of all non linear

programming problems. A fair number of functional relationships occurring in the real world are

truly quadratic. For example-Kinetic energy carried by a rocket or an atomic particle is

proportional to the square of its velocity. There are many non linear relationships occurring in

nature that are capable of being approximated by quadratic functions.

Consider a capacitated fixed charge bi-criterion indefinite quadratic transportation problem given

by



(P1): ij ij ij ij i ij ij

i I j J i I j J i I

min c x d x F , max t / x 0

i, j I J

Subject to

i ij i

j J

a x A

i I (1)

j ij jb x Bi I

j J (2)

i j i j i jl x u i, j I J (3)

ij i, j

i I j J i I j J

x P min A B

(4)

I = 1, 2 … m is the index set of m origins.

J = 1, 2… n is the index set of n destinations.

xij = number of units transported from origin i to the destination j.

cij = variable cost of transporting one unit of commodity from ith origin to the jth destination.

dij = the per unit damage cost or depreciation cost of commodity transported from the ith

origin to the jth destination.

lij and uij are the bounds on number of units to be transported from the ith origin to the jth

destination.

ai and Ai are the bounds on the availability at the ith origin, i I

bj and Bj are the bounds on the demand at the jth destination, j J

tij is the time of transporting goods from ith origin to the jth destination.

Fi is the fixed cost associated with ith origin.

For the formulation of Fi (i=1,2 … m), we assume that Fi (i = 1, 2 .. m) has p number of steps

so that

p

i il ill 1

F F

, i = 1, 2 … m



Where, il = 1 if Fi = n

ij il

j 1

x a

,l=1,2,3……..p, i=1,2,……m

= 0 otherwise

Here, 0 = ai1 < ai2 … < aip

ai1, ai2 …,< aip (i = 1,2, … m) are constants and Fil are the fixed costs. i= 1, 2 …m, l =

1,2 ..p

In the problem (P1), we need to minimize the total transportation cost and the depreciation cost

simultaneously. Also we need to minimize the fixed cost associated with ith origin and the time

of transportation from ith origin to jth destination. Sometimes, situations arise when one wishes to

keep reserve stocks at the origins for emergencies, there by restricting the total transportation

flow to a known specified level, say P i j

i I

min A , Bj J

.This flow constraint changes the

structure of the transportation problem.

In order to solve the problem (P1), we separate it in to two problems (P2) and (P3) where

(P2): minimize the cost function ij ij ij ij i

i I j J i I j J i I

c x d x F

subject to (1),(2),(3) and (4).

(P3): minimize the time function ij iji I , j Jmax t / x 0

subject to (1), (2), (3) and (4).

The flow constraint in the problem (P1) implies that a total i

i I

A P

of the source reserves

have to be kept at the various sources and a total j

j J

B P

of destination slacks is to be

retained at the various destinations. Therefore an extra destination to receive the source reserves

and an extra source to fill up the destination slacks are introduced.

In order to solve the problem (P2) we convert it in to a related problem (P2´) given below.

(P2´): ij ij ij ij i

i I j J i I j J i I

min Z c y d y F

subject to

'ij i

j J

y A

i I (5)



'ij j

i I

y B

j J (6)

ij ij ijl y u i, j I J (7)

m 1, j j j0 y B b j J

i , n 1 i i0 y A a i I

m 1, n 1y 0

Ai = Ai iI, A m+1 = j

j J

B -P , Bj = Bj jJ , Bn+1 = i

i I

A -P

cij = cij , iI, jJ, cm+1,j = ci,n+1 = 0 iI, jJ, cm+1,n+1 = M

díj = dij iI, jJ, dm+1,j = di,n+1 = 0 iI, jJ; d´m+1,n+1 = M

Fi = Fi i=1,2 …m, Fm+1 = 0

Where I = 1, 2 … m, m+1, J = 1, 2, … n, n+1

In order to solve the problem (P3), we convert it to a related problem (P3´) given

below.

(P3´): ij ijmin T max t / y 0 i I and j J subject to

'ij i

j J

y A

i I

'ij j

i I

y B

j J

ij ij ijl y u i, j I J

m 1, j j j0 y B b j J

i , n 1 i i0 y A a i I

m 1, n 1y 0

Ai = Ai iI, A m+1 = j

j J

B -P, Bj = Bj jJ , Bn+1 = i

i I

A -P

cij = cij , iI, jJ, cm+1,j = ci,n+1 = 0 iI, jJ, cm+1,n+1 = M

díj = dij iI, jJ, d´m+1,n+1 = M

tíj= tij i, j I J ,t´m+1,j = tí,n+1= 0 iI, jJ



t´m+1,n+1 > ij ijmax t / x 0 i I, j J

To obtain the set of efficient time cost trade off pairs, we first solve (P2´) and read the time with

respect to the minimum cost Z where time T is given by problem (P3´)

At the first iteration, let Z1* be the minimum total cost of the problem (P2) and T1

* be the

optimal time of the problem (P3) with respect to Z1* , then any schedule which is completed

earlier than T1* would cost more than Z1

* . So (Z1* , T1

*) is the first time cost trade off pair at the

first iteration.

After modifying the costs with respect to the time obtained, a new optimal cost is obtained and

time is read with respect to the new optimal cost .This procedure is called re-optimization

procedure. Let after q th iteration, the problem becomes infeasible. Thus, we get the following

complete set of time-cost trade off pairs.

(Z1*, T1*) ( Z2*, T2*),( Z3*,T3*),…………….( Zq*, Tq*) where Z1* ≤ Z2* ≤ Z3*≤………..≤

Zq* and T 1* ≥ T2* ≥ T3*………..≥ Tq* with strict inequality holding in atleast one of the two

conditions .The pairs so obtained are pareto optimal solutions of the given problem. Then we

identify the minimum cost Z1* and minimum time T q* among the above trade off pairs. The pair

(Z1*, T q*) with minimum cost and minimum time is termed as the ideal pair which can not be

achieved in practical situations.

3. THEORETICAL DEVELOPMENT:

Theorem 1: Let X = Xij be a basic feasible solution of problem (P2´) with basis matrix B.

Then it will be an optimal basic feasible solution if

1 2 1 1 2ij ij 1 ij ij 2 ij ij ij ij ij ij ij ij 1R z (d z ) z (c z ) (c z )(d z ) F 0 (i, j) N

And

2 1 2 2 1ij ij ij ij ij ij ij 1 ij ij 2 ij ij ij 2R (c z )(d z ) z (d z ) z (c z ) F 0 (i, j) N

Such that

1 1iji ju v c (i, j) B (8)

2 2iji ju v d (i, j) B (9)

1 1 1i j iju v z 1(i, j) N And N2 (10)



2 2 2i j iju v z 1(i, j) N And N2 (11)

ijF Is the change in fixed cost iFi I when some non basic variable xij enters the basis.

z1 = value of ij ij

i I j J

c x at the current basic feasible solution corresponding to the basis B.

z2 = value of ij ij

i I j J

d x at the current basic feasible solution corresponding to the basis B.

ij = level at which a non basic cell (i,j) enters the basis replacing some basic cell of B.

N1 and N2 denotes the set of non basic cells (i,j) which are at their lower bounds and upper

bounds respectively.

Note: 1 1 2 2i j i ju , v , u , v are the corresponding dual variables which are determined by using equations

(8) to (11) and taking one of the ui ,s or vj

,s. as zero.

Proof: Let z0 be the objective function value of the problem (P2).

Let z0 =z1z2 + F0 where F0 = iFi I

Let z

be the objective function value at the current basic feasible solution X

= xij

corresponding to the basis B obtained on entering the non basic cell xij N1 in to the basis which

undergoes change by an amount ij given by

minuij – lij ; xij - lij for all basic cells (i,j) with a (- )entry in the -loop; uij – xij for all basic

cells (i,j) with a (+ )entry in the -loop.

Then z

= 01 21 ij ij 2 ij ij ijij ijz c z z d z F F

z

- z0 = z1z2 + z2 ij (cij-z1

ij) + z1 ij (dij – z2ij) + 2

ij (cij-z1

ij) (dij – z2ij) - z1z2 + ijF

= ij [z2 (cij-z1

ij) + z1 (dij – z2ij) + ij (cij-z

1ij) (dij – z2

ij)]+ ijF

This basic feasible solution will give an improved value of z if z

< z0 .It implies that

ij [z2 (cij-z1

ij) + z1 (dij – z2ij) + ij (cij-z

1ij) (dij – z2

ij)]+ ijF < 0 (12)

Therefore one can move from one basic feasible solution to another basic feasible solution on

entering the cell (i,j) N1 in to the basis for which condition (12) is satisfied.

It will be an optimal basic feasible solution if



1 2 1 1 2ij 1 ij 2 ij ij ij ij ij 1ij ij ij ij ijR z (d z ) z (c z ) (c z )(d z ) F 0 (i, j) N

Similarly, when non basic variable xij N2 undergoes change by an amount ij then

z

- z0 = ij [ ij (cij-z1

ij) (dij – z2ij)- z2 (cij-z

1ij) - z1 (dij – z2

ij) +]+ ijF < 0

It will be an optimal basic feasible solution if

2 1 2 2 1ij ij ij ij 1 ij 2 ij ij 2ij ij ij ij ijR (c z )(d z ) z (d z ) z (c z ) F 0 (i, j) N

Definition: Corner feasible solution: A basic feasible solution yij i I´, j J´ to (P2´) is

called a corner feasible solution (cfs) if ym+1,n+1 = 0

Theorem 2. A non corner feasible solution of (P2´) cannot provide a basic feasible solution to

(P2).

Proof: Let yijI´ xJ´ be a non corner feasible solution to (P2´).Then ym+1,n+1 = (>0)

Thus i, n 1 i, n 1 m 1, n 1

i I i I

y y y

= i, n 1

i I

y

= i

i I

A P

(13)

i, n 1 i

i I i I

y A (P )

Now, for iI,

'ij ii

j J

ij i

i I j J i I

y A A

y A

(14)

(13) and (14) implies that ij

i I j J

y P

This implies that total quantity transported from the sources in I to the destinations in J is P +

> P, a contradiction to assumption that total flow is P and hence yijI´ xJ´ cannot provide a

feasible solution to (P2).

Lemma 1: There is a one –to-one correspondence between the feasible solution to (P2) and the

corner feasible solution to (P2´).



Proof: Let xijI xJ be a feasible solution of (P2).So xijI xJ will satisfy (1) to (4).

Define yijI´ xJ´ by the following transformation

yij = xij ,iI, j J

yi,n+1 = Ai - ij

j J

x , iI

ym+1,j = Bj - ij

i I

x , j J

ym+1,n+1 = 0

It can be shown that yij so defined is cfs to (P2´).

Relation (1) to (3) implies that

ij ij ijl y u for all iI, j J

i , n 1 i i0 y A a , iI

m 1, j j j0 y B b , j J

ym+1,n+1 ≥ 0

Also for iI

'ij ij i , n 1 ij i ij i i

j J j J j J j J

y y y x A x A A

For i = m+1

m 1, j ij m 1, n 1 j ij

j J j J j J i I

y y y (B x )

= j ij

j J i I j J

B x

= j

j J

B P

= A´m+1

'ij i

j J

y A

; i I

Similarly, it can be shown that 'ij j

i I

y B

; j J

Therefore yijI´ xJ´ is a cfs to (P2´).

Conversely, let yijI´ xJ´ be a cfs to (P2´).Define xij , iI, j J by the following transformation.

xij= yij , iI, j J



It implies that i j i j i jl x u , iI, j J

Now for iI, the source constraints in (P2´) implies

'ij i i

j J

y A A

ij i, n 1 i

j J

y y A

i ij i

j J

a y A

(Since 0 ≤ yi,n+1 ≤ Ai –ai , iI)

Hence, i ij i

j J

a x A

, iI

Similarly, for j J, j ij j

i I

b x B

For i= m+1

'm 1, j jm 1

j J j J

y A B P

m 1, j j

j J j J

y B P

Because ym+1,n+1 = 0

Now, for j J the destination constraints in (P2´) give

ij m 1, j j

i I

y y B

Therefore, ij m 1, j j

i I j J j J j J

y y B

ij j m 1, j

i I j J j J j J

y B y P

ij

i I j J

x P

Therefore xijI xJ is a feasible solution to (P2)

Remark 1: If (P2´) has a cfs, then since c´m+1,n+1=M and d´

m+1,n+1= M, it follows that non corner

feasible solution cannot be an optimal solution of (P2´) .

Lemma 2: The value of the objective function of problem (P2) at a feasible solution xijI x J is

equal to the value of the objective function of (P2´) at its corresponding cfs yijI´xJ´ and

conversely.

Proof: The value of the objective function of problem (P2) at a feasible solution xijI x J is



ij ij ij ij i

i I j J i I j J i I

c x d x F

'ij ij ij ij i

i I j J i I j J i I

c y d y F

Because

'ij,ij

ij ij,

' 'i,n+1 m+1, j

' 'i,n+1 m+1, j

m 1,n 1

' 'im+1 i

c = c i I, j J

x = y i I, j J

c = c = 0; i I, j J

d = d = 0; i I, j J

y 0

F = 0, F = F , i I

= the value of the objective function of (P2´) at the corresponding cfs yijI´xJ´

The converse can be proved in a similar way.

Lemma 3: There is a one –to-one correspondence between the optimal solution to (P2) and

optimal solution to the corner feasible solution to (P2´).

Proof: Let ij I Jx

be an optimal solution to (P2) yielding objective function value z0 and

ij I Jy

be the corresponding cfs to (P2´). Then by Lemma 2, the value yielded by ij I Jy

is z0

..If possible,let ij I Jy

be not an optimal solution to (P2´). Therefore, there exists a cfs 'ijy to

(P2´) with the value z1 < z0. Let 'ijx be the corresponding feasible solution to (P2).Then by

lemma 2,

' 'ij ij iij ij

i I j J i I j J i I

c x d x F

= z1, a contradiction to the assumption that ij I Jx

is an

optimal solution of (P2).Similarly, an optimal corner feasible solution to (P2´) will give an

optimal solution to (P2).

Theorem 3: Optimizing (P2´) is equivalent to optimizing (P2) provided (P2) has a feasible

solution.

Proof: As (P2) has a feasible solution, by lemma 1, there exists a cfs to (P2´).Thus by remark 1;

an optimal solution to (P2´) will be a cfs. Hence, by lemma 3,an optimal solution to (P2) can be

obtained.

4. ALGORITHM:



Step1: Given a capacitated fixed charge bi-criterion indefinite quadratic transportation problem

with restricted flow (P1), separate the problem (P1) in to two problems (P2) and (P3).Form the

related transportation problems (P2´) and (P3´).Find a basic feasible solution of problem (P2´)

with respect to variable cost only. Let B be its corresponding basis.

Step 2: Calculate the fixed cost of the current basic feasible solution and denote it by F(current)

Where F (current) = m

i

i 1

F

Step 3(a): Find ijF F ( N B ) F(curren t ) where F (NB) is the total fixed cost obtained

when some non basic cell (i,j) enters the basis.

(b) Calculate ij ,(cij-z1

ij) , (dij – z2ij), z1, z2 for all non basic cells such that

1 1iji ju v c (i, j) B

2 2iji ju v d (i, j) B

1 1 1i j iju v z 1(i, j) N And N2

2 2 2i j iju v z 1(i, j) N And N2

z1 = value of ij ij

i I j J

c x at the current basic feasible solution corresponding to the basis B

z2 = value of ij ij

i I j J

d x at the current basic feasible solution corresponding to the basis B.

ij = level at which a non basic cell (i,j) enters the basis replacing some basic cell of B.



Note: 1 1 2 2i j i ju , v , u , v are the dual variables which are determined by using the above equations and

taking one of the ui, s or vj, s. as zero.

(c) Find 11ijR (i, j) N and 2

2ijR (i, j) N where

1 2 1 1 2ij 1 ij 2 ij ij ij ij ij 1ij ij ij ij ijR z (d z ) z (c z ) (c z )(d z ) F 0 (i, j) N

and

2 1 2 2 1ij ij ij ij 1 ij 2 ij ij 2ij ij ij ij ijR (c z )(d z ) z (d z ) z (c z ) F 0 (i, j) N





Step 4: If 11ijR 0 (i, j) N and 2

2ijR 0 (i, j) N then the current solution is optimal to (P2´).Go

to step 5.Otherwise, some (i,j) N1 for which 1ijR 0 or some (i,j) N2 for which 2

ijR 0 will

enter the basis. Go to step 2.

Step 5: Let Z1 be the optimal cost of (P2´) yielded by the basic feasible solution y´ij.

Step 6: Find T1 where T1 = maxtij /y´ij > 0 from the problem (P3´).Then the corresponding

pair (Z1 , T1 ) will be the first time cost trade off pair for the problem (P1).To find the next best

time-cost trade off pair, go to step 7.

Step7: Define cij1 = M if tij ≥T1

cij if tij < T1

where M is a sufficiently large positive number. Form the corresponding capacitated fixed

charge quadratic transportation problem with variable cost 1ijc .Repeat the above process till the

problem gets infeasible. The complete set of time cost trade off pairs of (P1) at the end of qth

iteration are given by (Z1,T1),(Z2,T2)……….(Zq,Tq) where Z1 ≤ Z2 ≤ …..≤ Zq and T1 ≥T2

≥……≥Tq. with strict inequality holding in atleast one of the two conditions.

Remark 2: The pair (Z1, Tq) with minimum cost and minimum time is the ideal pair which

cannot be achieved in practice except in some trivial case.

Convergence of the algorithm: The algorithm will converge after a finite number of steps

because the choice of cij, s in step 7 will ensure an infeasible solution after a finite number of

iterations.

5. NUMERICAL ILLUSTRATION:

Consider a 3 x 3 capacitated fixed charge bi-criterion indefinite quadratic transportation

problem with restricted flow .Table 1 gives the values of cij, dij, Ai ,Bj for i=1,2,3 and j=1,2,3



Table 1: cost matrix of problem (P2)

D1 D2 D3 Ai

O1 5

9

9

30

O2 4

3

6

7

2

4

40

O3 2

2

1

9

1

4

50

Bj 30 20 30

Note: values in the upper left corners are cij ,s and values in lower left corners are dij

,s for

i=1,2,3.and j=1,2,3.

Also, 3 ≤ 3

1j

j 1

x ≤ 30, 10≤

3

2j

j 1

x ≤40, 10 ≤

3

3j

j 1

x ≤ 50, 5≤

3

i1

i 1

x ≤30 ,

5≤ 3

i2

i 1

x ≤ 20, 5 ≤

3

i3

i 1

x ≤ 30

1≤ x11 ≤ 10 , 2 ≤ x12 ≤ 10 , 0 ≤ x13 ≤ 5 ,0≤ x21 ≤ 15 , 3 ≤ x22 ≤ 15 , 1 ≤ x23 ≤ 20 , 0≤ x31≤ 20 ,

0≤ x32≤ 13, 0≤ x33≤ 25

F11= 100, F12 = 50, F13 = 50, F21 = 150, F22 = 100, F23 = 50, F31= 200, F32= 150, F33 = 100

Fi = 3

il il

l 1

F

where for i= 1, 2, 3

il = 1 if 3

ij

j 1

x 0

0 otherwise



i2 = 1 if 3

ij

j 1

x 10

0 otherwise

i3 = 1 if 3

ij

j 1

x 20

0 otherwise

Table 2 gives the values of t ij, s for i=1, 2, 3 and j=1, 2, 3

Table 2: Time matrix of problem (P3)

D1 D2 D3

O1 15 8 13

O2 10 13 14

O3 12 10 9

Let the restricted flow be P = 40 where P = 40 < min 3 3

i j

i 1 j 1

A 120, B 80

Introduce a dummy origin and a dummy destination in Table 1 with ci4 = 0 = d i4 for all i = 1,2 ,3

and c4j = 0 = d4jfor all j = 1,2,3 . c44=d44=M where M is a large positive number. Also we have

0≤ x14 ≤ 27 , 0≤ x24 ≤ 30 , 0 ≤ x34 ≤ 40 , 0 ≤ x41 ≤ 25 , 0 ≤ x42 ≤ 15 , 0 ≤ x43 ≤ 25 and F4j = 0 for

j=1,2,3,4 In this way , we form the problem (P2´).Similarly on introducing a dummy origin and a

dummy destination in Table 2 with ti4 = 0 for i=1,2 ,3and t4j= 0 for j=1,2,3,

t44 > ij ijmax t / x 0 i I, j J ,we form problem (P3´) . Also, B4 = 3

i

i 1

A P

=120-40 = 80

and A4= 3

j

j 1

B P

= 80-40 = 40

Now we find an initial basic feasible solution of problem (P2´) which is given in table 3 below.



Table 3: A basic feasible solution of problem (P2´)

D1 D2 D3 D4 1iu 2

iu F(current)

O1 5 1

4

9 2

2

9

1

0 27

0

1 4 100

O2 4

3

6 3

7

2 7

4

0 30

0

2 4 150

O3 2 20

2

1

9

1 7

4

0 23

0

1 4 450

O4

0 9

0

0 15

0

0 16

0

M

M

0 0 0

vj1

0 0 0 -1

vj2

0 0 0 -4

Note: entries of the form a and b represent non basic cells which are at their lower and upper

bounds respectively. Entries in bold are basic cells.

F (current) = 700, z1 = 102, z2 = 125

Table 4: Computation of 1ijR , 2

ijR

NB O1D1 O1D2 O1D3 O2D1 O2D2 O2D4 O3D1 O3D2

ij 7 7 5 6 6 7 16 7

1ij ijc z 4 8 8 2 4 -1 1 0

2ij ijd z 0 -2 -3 -1 3 0 -2 5

F(NB) 600 600 700 700 700 700 700 700

ijF -100 -100 0 0 0 0 0 0

1ijR 3400 4688 2870 816 5268 3570

2ijR 875 752



Since 1ijR ≥ 0 1(i, j) N and 2

2ijR 0 (i, j) N , the solution in table 3 is an optimal solution

of (P2´) and hence yields an optimal solution of (P2).Therefore minimum cost = (102 x 125) +

700 = 13450 and corresponding time is T1 = 15. Hence the first time cost trade off pair is (13450,

15)

Define 1ijc =

1ij

1ij ij

M if t T 15

c if t < T 15

and solving the resulting problem, the next trade off pair is

(13450, 14). Similarly, the other pairs are (14266, 13), (14266, 12), (16500, 10).

6. CONCLUSION:

In order to solve a capacitated fixed charge bi – criterion indefinite quadratic transportation

problem, given problem is separated in to two problems. One of them being an indefinite

quadratic transportation problem has its optimal solution at an extreme point. After calculating

the cost, corresponding time is read. This is the first cost time trade off pair. Proceeding likes this

we get the various trade off pairs.

REFERENCES

[1] Arora, S.R., Khurana, A., “A paradox in an indefinite quadratic transportation problem”,

International Journal of Management and Systems, 18, (2002), 301-318

[2] Arora, S.R., Khurana, A., “Three dimensional fixed charge bi – criterion indefinite quadratic

transportation problem”,Yugoslav Journal of Operations Research,14(1),(2004),83-97

[3] Arora, S.R., Thirwani, D., Khurana, A.,“An algorithm for solving fixed charge bi – criterion

indefinite quadratic transportation problem with restricted flow”, International Journal of

optimization: Theory, Methods and Applications,1(4),(2009),367-380

[4] Basu, M, Pal, B.B and Kundu, A., “An algorithm for the optimum time cost trade off in a

fixed charge bi-criterion transportation problem’’, Optimization, 30, (1994), 53-68



[5] Bhatia, H.L, Swarup, K and Puri , M.C., ‘‘Time cost trade off in a transportation problem’’,

Opsearch, 13(3-4),(1976),129-142

[6] Bit, A.K. Biswal, M.P. , Alam, S.S., “Fuzzy Programming technique for multi- objective

capacitated transportation problem” , Journal of Fuzzy Mathematics,1(2),(1993),367-376

[7] Dahiya, K. and Verma, V., ‘‘Capacitated transportation problem with bounds on rim

conditions’’, Europeon journal of Operational Research, 178, (2007), 718-737

[8] Hirisch, W.M. and Dantzig, G.B., ‘‘the fixed charge problem’’, Naval Research Logistics

Quarterly, 15(3), (1968), 413-424

[9] Khanna,S. , Thirwani,D. and Arora, S.R., ‘‘An algorithm for solving fixed charge bi –

criterion transportation problem with restricted flow”, Optimization, 40,(1997),193-206



IMPACTS OF USE OF RFBIDW ON TAXATION

Prof Sulatan Singh*

Prof Surendra Kundu**

Ms. Madhu Arora**

ABSTRACT

The CBDT is statutory authority for policy and planning of direct taxes in India.Business

intelligence (BI) mainly refers to computer-based techniques used in identifying, extracting, and

analyzing business data, such as sales revenue by products and/or departments, or by associated

costs and incomes.Computerized processing of returns all over the country introduced in 2002.

To enhance revenue realization and catch tax evaders quickly, the Central Board of Direct Taxes

is working on a comprehensive data warehousing system which will transform the functioning of

the Income Tax Department called Revenue Forecasting & Business Intelligence Data

Warehouse(RFBIDW).From data pertaining to mobile users to electoral records and database of

high net worth individuals, a universe of diverse information will be assembled in the I-T

warehouse for analysis and generating credible information and reports for investigation

purposes and revenue forecasting. Present study conceptual in nature is based on analyzing

impact of RFBIDW on taxation and found that it will be a remarkable step if used honestly and

intelligently.

*Chairman, CDLU, Sirsa

**Professor, CDLU, Sirsa

***Research Scholar, CDLU, Sirsa



INTRODUCTION

Kautilya’s Arthasastra was the first authoritative text on public finance, administration and the

fiscal laws in this country. His concept of tax revenue and the on-tax revenue was a unique

contribution in the field of tax administration. It was he, who gave the tax revenues its due

importance in the running of the State and its far-reaching contribution to the prosperity and

stability of the Empire. It is truly a unique treatise. It lays down in precise terms the art of state

craft including economic and financial administration.

The introduction of electronic filing of I-T returns, e-payment of taxes, establishment of the

national network (TAXNET), and consolidation of the Regional Computer Centers into the

National Data Center have laid the foundation for the next generation administrative reforms in

the Department with the Computerised processing of returns all over the country introduced in

2002.Net direct tax collection in the current financial year is higher by 6.7% at R1,27,858croreas

against R1,19,849 crore collected from 1st April to 15thSeptember last year. The net collection

has been impacted by R61, 000crore of refunds. Gross direct tax mop-up duringthe period has

been R1,88,868crore, a growth of 29.5% over the previous year’s collection during the period of

R1,45,825crore.(Source: http://www.indianexpress.com) this can be increased to standards if

government shift attention from individual assessed to groups such as families, business groups,

trades, dealers in particular items and intermediaries for curbing tax evasion.


The design of the research helps to get the ways for doing the work. Summary of the proposed

research work is given as under:.

As the purpose of research is to discover answers to questions through the application of

scientific procedures, research objectives can be one of the following categories:

1. Exploratory research to gain familiarity with a phenomenon or to achieve new insights

into it.

2. Descriptive research is to portray accurately the characteristics of a particular individual,

situation or a group.



3. Diagnostic research is to determine the frequency with which something occurs or with it

is associated with something else.

4. Hypothesis testing research to test a hypothesis of a causal relationship between variables

Present study is conceptual in nature research of an exploratory r

OBJECTIVES OF THE STUDY:

i. To study about the present system for business intelligence for tax used.

ii. To analyze the concept of RFBIDW

iii. To understand impacts of using RFBIDW on present system

iv. To suggest changes if any for improvement of proposed data warehouse.

Data Collection:

Secondary data available on official website of CBDT, journals, newspapers and books has been

considered for studyhas been duly acknowledged in references.

Time period: This study has been done in October-November 2011.data after study may vary due

to vastness and changing nature of subject.

Limitation of the study:

Due to vastness, time bound and complexity of subject only RFBIDW is main focus of the study.

Innovations in future may provide scope for future researchers in this context.

Analysis

Common functions of business intelligence technologies are reporting, online analytical

processing, analytics, data mining, process mining, complex event processing, business

performance management, benchmarking, and text mining and predictive analytics. Information

available with the ministry of corporate affairs, select data from excise and Customs and the

Goods and Services Tax, customised data from think-tanks such as CMIE and data received from

other enforcement agencies in India and abroad, will also be available at the facility, to be known

as the Revenue Forecasting & Business Intelligence Data Warehouse (RFBIDW).



Table 1:

External data Internal data Base

RFBIDW Information on PAN

e-filing data

tax deduction at source

share transaction tax payment

annual information return on high value

transaction

specific information gathered by central

information branch

With this, RFBIDW is also expected to have certain locally relevant information, especially for

investigation, and also specialized database on venture intelligence, trade analyst reports, equity

analysis and fiscal reports.

According to an internal estimate of the department, the size to be handled by the I-T warehouse

could be around four billion data pieces. The Integrated Taxpayer Database Management System

alone has over 600 million pieces of information, mobile numbers would throw up around 1.2

billion data pieces and PAN database had 120 million entries. Besides, there would be local data

and also information gathered from different sources.

The idea behind RFBIDW was to shift attention from individual assesse to groups such as

families, business groups, trades, dealers in particular items and intermediaries for curbing tax

evasion.

By using the warehouse, the risk assessment wing of the department would prepare and update

the database created on suspect intermediaries and known offenders and also organized schemes

of tax avoidance and evasion.



Table 2:

Examples of tax evasion

failing to report all income

claiming deductions for expenses not incurred or legally deductible

claiming input credits for goods or services that GST has not been paid on

not reporting cash wages

not forwarding tax withheld from employee's wages to the ATO

not withholding tax from a worker's wages (for example, paying in cash)

not paying employee super entitlements

not lodging tax returns in an attempt to avoid payment

Not lodging a tax return to avoid child care or other obligation.

Tax evasion is an activity commonly associated with businesses that use cash transactions, which

gives them the opportunity not to declare it and pay tax on it.Investigation unit of the department

would be able to quickly develop a 360-degree profile of suspected tax evaders from RFBIDW

information and intelligence. The forecasting section would prepare reports on the basis of

RFBIDW data on the revenue potential in specific areas and provide inputs for policy decisions.

Table 3:

Data from following sources will be cleaned and profiled:

SOURCES DATA

INTERNAL DATABASES PAN / E-Filing / TDS, OLTAS, CIB,

Annual Information Return, Share

Transaction Tax

EXTERNAL DATABASES Mobile phone, MCA database, GST /

Excise / Customs, CMIE, Capital Line, Other

Enforcement



agencies, Current / alternate addresses

LOCAL DATABASES Locally relevant databases with specific

relevance for investigation purposes

SPECIALIZED DATABASE Venture Intelligence, Trade Analyst

Reports, Equity Analysis Reports, Fiscal

Reports etc

MIS Reports Analytic Reports

Data

Findings and Suggestions

Kautilya has also described in great detail the system of tax administration in the Mauryan

Empire People who were suffering from diseases or were minor and students were exempted

from tax or given suitable remissions. The revenue collectors maintained up-to-date records of

collection and exemptions. The total revenue of the State was collected from a large number of

sources as enumerated above. There were also other sources like profits from Stand land (Sita)

religious taxes (Bali) and taxes paid in cash (Kara). Vanikpath was the income from roads and

traffic paid as tolls. If RFBIDW is used honestly and intelligently its 360 degree profile will be

useful to detect black money and tax evasions. It will cover a large section of society and will not

consider small groups, individual assess. Plans are afoot to assemble critical data from various

sources under one umbrella to nab tax evaders and better policy-making.

REFERNCES:

NEWSPAPERS

BUSINESS STANDARD SEPTEMBER 14, 2011



1. http://www.business-standard.com/india/news/cbdts-business-intelligence-data-warehousing-to-

boost-tax-mop-up/449094/

2. http://en.wikipedia.org/wiki/Business_intelligence

3. http://www.information-management.com/white_papers/1210202-

htmlhttp://www.cainindia.org/news/9_2011/cbdts_business_intelligence_data_warehousing_to_b

oost_tax_mopup.html

4. http://incometaxindia.gov.in/ccit/CBDT.asp:

5. http://www.indianexpress.com

6. http://www.incometaxindia.gov.in/archive/BreakingNews_FMSpeech_05312010.pdfhttp:

//www.business-standard.com/india/)

7. http://www.ato.gov.au/corporate/content.aspx?doc=/content/30331.htmhttp://www.incom

etaxindia.gov.in/HISTORY/PRE-1922.ASP



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EVALUATION OF KNOWLEDGE MANAGEMENT LEVEL OF

EDUCATIONAL INSTITUTIONS USING FCE AND AHP

Mohit Maheshwarkar*

Dr. N. Sohani**

Pallavi Maheshwarkar***

ABSTRACT

Knowledge Management (KM) comprises a range of strategies and practices used in an

organization to identify, create, represent, distribute, and enable adoption of insights and

experiences. Such insights and experiences comprise knowledge, either embodied in individuals

or embedded in organizational processes or practice. Today many enterprises’ main profit

gradually relies on the innovation, which should be established on the knowledge management

system. However, the cost of executing the project of knowledge management is always high, and

to build up a set of effective criterion to realize the achievement of the project is significant. This

research bases on the key success factors of the KM project and applies to the Fuzzy

Comprehensive Evaluation (FCE) and Analytical Hierarchy Process (AHP) to calculate the level

of Knowledge Management for Educational Institutions.

Keywords: Knowledge Management, FCE, AHP.

*Assist. Professor, R.I.T, Indore (M.P)

**Reader, I.E.T, D.A.V.V. , Indore (M.P)

***Assist. Professor, P.I.T.S, Ujjain (M.P)



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I. INTRODUCTION




or embedded in organizational processes or practice. Knowledge management is a management

whose core is knowledge, and a series of process management that is collections, organization,

innovation, diffusion, use and development of knowledge on which production and operation of

enterprises relies. It is a management philosophy and methods, through the systematic use of

information content, processes and expert skills; it can improve the innovative capability of

enterprises and rapid response capability. Knowledge management is a process. The content of

knowledge management includes the contents of a system, not only referring only to a particular

aspect. The main content of knowledge management should include four parts: knowledge

acquisition, knowledge management systems, knowledge sharing, and knowledge utilization.

These four sections are closely connected, interdependent and mutually reinforcing. Educational

Institutions face huge competition.Due to the introduction of competition in the market, these

Educational Institutions face unprecedented challenges. Therefore, KM is of extreme importance

to these institutions.

II. EVALUATION OF EDUCATIONAL INSTITUTIONS’ KNOWLEDGE

MANAGEMENT LEVEL

Knowledge management underlines the learning and inheritance of human knowledge, and

emphasize on creation, accumulation, use and updates of internal knowledge. Through the

implementation of knowledge management, colleges can update and manage their knowledge

innovation to create favorable conditions and environment, and can achieve the best combination

and effective use of the knowledge of their faculty members .Therefore, the introduction of

knowledge management theory to these institutions is the only way to survival and development.

To gain a leading edge in the competition, colleges faced with the primary task is to enhance the

ability of individual faculty members. Through the strengthening and aggregation of individual

capacities, we can improve the overall organization's ability to win competitive advantage in the

management, knowledge and talent areas. The Educational Institutions perform a difficult task of



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handling the future of the country.They provide services which lead and represent the nation at

the global level. The evaluation of level of knowledge management is the important work which

should be considered as a primary task from educatioal point of view for the country.In the

evaluation the level of a college’s knowledge management, the objective has great significance

for the development of facilities provided to the students. For this purpose we follow the

principles of scientific, systematic, hierarchical nature, practicality and operability.

III. ANALYTICAL HIERARCHY PROCESS

The Analytic Hierarchy Process (AHP) is a structured technique for helping people deal with

complex decisions. Rather than prescribing a "correct" decision, the AHP helps people to

determine one. An AHP hierarchy is a structured means of describing the problem at hand. It

consists of an overall goal, a group of options or alternatives for reaching the goal, and a group

of factors or criteria that relate the alternatives to the goal. In most cases the criteria are further

broken down into sub criteria, sub-sub criteria, and so on, in as many levels as the problem

requires (Fig. 1).The hierarchy can be visualized as a diagram like the one below, with the goal

at the top, the alternatives at the bottom, and the criteria filling up the middle. In such diagrams,

each box is called a node. The boxes descending from any node are called its children. The node

from which a child node descends is called its parent. Applying these definitions to the diagram

below, the five Criteria are children of the Goal, and the Goal is the parent of each of the five

Criteria. Each Alternative is the child of each of the Criteria, and each Criterion is the parent of

three Alternatives.

Fig. 1 – Hierarchical Structure for AHP (Thomas L. Saaty, 2008)



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Once the hierarchy is built, the decision makers systematically evaluate its various elements,

comparing them to one another in pairs. In making the comparisons, the decision makers can use

concrete data about the elements, or they can use their judgments about the elements' relative

meaning and importance. It is the essence of the AHP that human judgments, and not just the

underlying information, can be used in performing the evaluations. For this purpose a pair wise

comparison scale is used, which is shown in the Table 1 given below. After that AHP converts

the evaluations to numerical values that can be processed and compared over the entire range of

the problem. A numerical weight or priority is derived for each element of the hierarchy,

allowing diverse and often incommensurable elements to be compared to one another in a

rational and consistent way. This capability distinguishes the AHP from other decision making

techniques. In the final step of the process, numerical priorities are derived for each of the

decision alternatives. Since these numbers represent the alternatives' relative ability to achieve

the decision goal, they allow a straightforward consideration of the various courses of action.

Table.1– Pair Wise Comparison Scale (Thomas L. Saaty, 2008)

Saaty (2008) developed the following steps for applying AHP:

i. Define the problem and determine its goal,



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ii. Structure the hierarchy with the decision maker’s objective at the top with the

intermediate levels capturing criteria on which subsequent levels depend and the bottom

level containing the alternatives, and

iii. Construct the set of n× n pair wise comparison matrices for each to the lower levels with

one matrix for each element in the level immediately above. The pair wise comparisons

are made suing the relative measurement scale (as discussed above). The pair wise

comparisons capture a decision maker’s perception of which element dominates the

other.

iv. There are n(n-1)/2 judgments required to develop the set of matrices in step 3.

Reciprocals are automatically assigned in each pair wise comparison.

v. The hierarchy synthesis function is used to weight the eigenvectors by the weights of the

criteria and the sum is taken over all weighted eigenvector entries corresponding to those

in the next lower level of the hierarchy.

vi. After all the pair wise comparisons are completed, the consistency of the comparisons is

assessed by using the Eigen value, λ, to calculate a consistency index, CI:

CI = (λ-n)/ (n-1).

Where n is the matrix size. Judgment consistency can be checked by taking the

consistency ratio (CR) of CI with the appropriate value in table 2, given below. Saaty

[1980] suggests that the CR is acceptable if it does not exceed 0.10. If the CR is greater

than 0.10, the judgment matrix should be considered inconsistent. To obtain a consistent

matrix, the judgments should be reviewed and repeated.



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Table.2- Average Random Consistency Index

Size of

Matrix 1 2 3 4 5 6 7 8 9 10

Random

Consistency 0.00 0.00 0.58 0.90 1.12 1.24 1.32 1.41 1.45 1.49

IV. LITRETURE REVIEW

Robert G. and Eure P.E (2009) tell that Knowledge needs to be managed by the enterprise as an

enterprise asset. They also focus on knowledge management. According to them Knowledge

management provides tools to achieve optimum effectiveness. They also insisted to include the

KM as a topic in the Systems Engineering Handbook. Rizwana Irfan and Maqbool uddin-Shaikh

(2010) find that data and knowledge coming from heterogeneous sources and formats are

required to be efficiently extracted, transformed and stored for decision making. Their proposal

provides qualitative approach for enhancing the existing conceptual model for knowledge

processing to do transformation.

NIU Dongxiao and LI Jianqing (2010) investigate that Knowledge management is a process to

improve the competitiveness of enterprises and identify the knowledge, acquire it and play its

full role in the process. Knowledge Management is a new tool in management studies and a

powerful tool for the development, use and sublimation of enterprise knowledge resources. They

conclude that if the power generation companies want to sustain competitive advantage in the

knowledge economy era, they should be started a developed corporate culture based on

knowledge management-oriented as soon as possible, so that the organization's innovative

capacity and creativity of staff's personal mutually promote and make common progress. Qian-

Wang Deng and Yong-Zheng Tian (2008) used an approach of integrating knowledge

management process models into product development process models. In the approach, a

method named knowledge-based engineering process model is adopted as the method of



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modeling a product development process. To realize the integration between knowledge

management process model sand the product development process models, a basic rule,

considering the knowledge management process as a special kind of sub-process in product

development processes, is followed. Maryam Alavi and Dorothy E. Leidner (1999) focus on

achieving the correct amount and type of accurate knowledge and garnering support for

contributing to the Knowledge Management System (KMS). Yang Tong (2009) classifies and

concludes the risks existed in knowledge management from a view of identification. The

research has been divided into following aspects of knowledge assets at risk: the risk of

knowledge spillovers, knowledge conversion risk, the risk of wastage, leakage risks, contractual

risks, moral hazard from Knowledge and knowledge of risk vector.

Thomas L. Saaty (2008) tells that the Analytic Hierarchy Process (AHP) is a theory of

measurement through pair wise comparisons and relies on the judgments of experts to derive

priority scales. It is these scales that measure intangibles in relative terms. The comparisons are

made using a scale of absolute judgments that represents how much more; one element

dominates another with respect to a given attribute. The judgments may be inconsistent, and how

to measure inconsistency and improve the judgments, when possible to obtain better consistency

is a concern of the AHP. The derived priority scales are synthesized by multiplying them by the

priority of their parent nodes and adding for all such nodes. He also tells that Analytic Hierarchy

Process (AHP) is a theory of relative measurement with absolute scales of both tangible and

intangible criteria based on the judgment of knowledgeable and expert people. How to measure

intangibles is the main concern of the mathematics of the AHP. The AHP reduces a

multidimensional problem into a one dimensional one. Decisions are determined by a single

number for the best outcome or by a vector of priorities that gives an ordering of the different

possible outcomes. We can also combine our judgments or our final choices obtained from a

group when we wish to cooperate to agree on a single outcome.

Jay Liebowitz (2005) discusses about the novel approach in applying the analytic hierarchy

process (AHP) to generate the ratio scores for the valued graphs to be used in Social Network

Analysis (SNA) in order to develop a knowledge map of the organization. According to him it

quantifies subjective judgments used in decision-making, and has been applied in numerous

applications throughout the world. Kamal M. Al-Subhi and Al-Harbi (2001) tell that the



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Analytical Hierarchy Process (AHP) as a potential decision making method for use in project

management. They used contractor prequalification problem as an example. For this a

hierarchical structure is constructed for the prequalification criteria and the contractors wishing

to prequalify for a project. They found that by applying the AHP, the prequalification criteria can

be prioritized and a descending-order list of contractors can be made in order to select the best

contractors to perform the project. Their paper presents group decision-making using the AHP.

Heung-Suk Hwang et al. (2005) used a supplier selection analysis model with the help of AHP

method.

V. THE EVALUATING MODEL CONSTRUCTION

When enterprises evaluate a thing, which have n index factors, they are marked as

c1,c2,c3………………… cn. These index factors compose a finite set C.

C = c1,c2,c3………..cn

According to actual needs, the revies are divided into m degree v1,v2,v3………..vm. they

compose a finite set of reviews V.

V= v1,v2,v3……………..vm

When enterprises need to value a thing from a several different aspects, te result is compressive.

The result is a fuzzy set B from reviews set V. Because V is a finite set, B is also a finite set.

B = b1/v1+ b2/v2 + b3/v3+bm/vm. (1)

It abbreviate as m dimension fuzzy vectors:

B= b1, b2, b3………………bm

Its case is V, and bj is the membership of the corresponding elements in B and bj Є [0,1] =

1,2,3…………m.

In the actual evaluating, the importance of each element is different. This is an objective fact.

The set of factors is fuzzy one. A, which is the elements set U in the case; A is also a finite set.

So the factor set is also a finite fuzzy set.



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A = a1/c1 + a2/c2 +

a3/c3……………………. an/cn

Similarly, A can also be said by n-

dimensional fuzzy vectors.

A = (a1, a2, a3………………… an)

Its case us C, ai is the membership

of the corresponding elements in A, ai Є

[0, 1], Σi=1n ai = 1.

The fuzzy comprehension evaluation is to optimize the fuzzy set A by fuzzy relation B = AR

B= A.R = (a1, a2, a3………..an).

This is fuzzy comprehension evaluation model. B is the result of the fuzzy comprehension

evaluation, and it is m- dimensional fuzzy row vectors; A is the weight set of the model, and it is

n- dimensional fuzzy row vectors; R is the fuzzy relations from C to V, and it is a n×m matrix, in

which the rij is the possibility of remark j for element i.(Ting Wang at el.2010)

VII. CASE STUDY

Here the Educational Institutions selected for the analysis are three in nos. and all are the

engineering institutions. The basic reason behind this selection is that today, the students of

these collages are facing a lot of problems regarding their studies, faculties, practicals provided

by the institution etc. In this paper we test the knowledge management level of colleges’ on

the anvil of different criteria. The selected criteria are : Teaching Practices, Practical Training

and Examination Pattern. These criteria are sub divided in sub criteria the details of which are

given as follows. Fig.3 shows the hierarchical structure.

r11 r12 ……. r1m

r 21 r22 …….. r2m

:

:

:

:

:

:

:

:

r n1 r n2 …….. rnm



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Fig.2 – Hierarchical Structrue for Knowledge Management Level Evaluation

Conceptual teaching by the faculty: It defines how serious is the faculty about the concept

making of the student.

Expert Lectures: Expert lectures provide easy to grasp approach and make the students

aware of the current practices running on in the company.

Level of study material provided: The study material provided/ suggested should be such

that it should not be treated as bunch of useless papers by the students.

Levels of practicals conducted: Practicals conducted should not fulfill only the basic

requirements of the syllabus. Practicals should be designed in order to make the concepts

of the students clearer about the subject.

No. of practicals conducted: Numbering of the practicals conducted should be such that it

should clear almost each topic of the syllabus.

Educational Visits: These are directly hand to mouth approach and should not be

neglected or underestimated in any case.



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Projects delivered and guided: Projects delivered for submission must be carefully

analyzed and reviewed by the departmental faculty members before assigning the

students.

Level of question paper: Initial test paper designed for the students should be easy in

order to see where the student is lacking. After problem Remidification, the later stages

of the question paper may be modified on the basis of complexity.

Frequency of tests: The tests carried out by the institution should not daily but frequently.

Problem Remidification: After declaring the test’s results, each of the paper must be

shown before the students in the class and there should be a large problem solving

session in order to magnify the problems of the students.

The detailed evaluation plan is given as follows:

A. Determine the reviews set, V= Strongest, Stronger, Strong, Weak and Weaker to

determine the KM level. The factors are constructed on the basis of examination of the

education system analyzed by various experts, faculty members, students and parents.

B. Comparison matrix is constructed according to hierarchical structure model for one

institution. Here, in this paper we have chosen total no. of institutions as three out of

which evaluation details of one institution are provided. The analysis of others will be

similar to the first one.

Table.2- Comparison matrix for C- Ck

C C1 C2 C3 W

C1 1 1/5 1/3 0.1042

C2 5 1 3 0.6372

C3 3 1/3 1 0.2583



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Σ 9 1.5333 4.333 1.000

λ max = 3.0341, CI = 0.0179, RI= 0.58, CR = 0.0332 < 0.10

Table.3 - Comparison Matrix for Ck- Cij

C C11 C12 C13 W

C11 1 1/3 1/5 0.1061

C12 3 1 1/3 0.2604

C13 5 3 1 0. 6334

λ max = 3.0385, CI = 0.0192, RI= 0.58, CR = 0.0332 < 0.10

Table.4 - Comparison Matrix for C2- Cij

C C21 C22 C23 C24 W

C21 1 3 1/3 1 0. 20087

C22 1/3 1 1/5 1/3 0.07885

C23 3 5 1 3 0.51941

C24 1 3 1/3 1 0.20087

λ max = 4.0428, CI = 0.01426, RI= 0.90, CR = 0.0158 < 0.10

Calculations for λ max, CI, RI and CR:

λ max = 9(0.1042) + 1.5333(0.6372)+ 4.333(0.2583) = 3.0341

CI = (3.0358- 3)/2 = 0.0179

RI = 0.58 (From Table.1)

& CR = CI/RI = 0.0179/0.58 = 0.030 < 0.10



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Table.5 - Comparison Matrix for C3- Cij

C C1 C2 C3 W

C1 1 1/5 1/3 0.1042

C2 5 1 3 0.6372

C3 3 1/3 1 0.2583

λ max = 3.0341, CI = 0.0179, RI= 0.58, CR = 0.0332 < 0.10

C. Students, parents and faculty members gave their opinions on the basis of questionnaire

given to them for the purpose of evaluation of level of knowledge management. On the

basis of these opinions, experts give the weights to different colleges.

Table.6-Weights for Teaching Practices

Ck TEACHING PRACTICES (1.042)

Cij 0.1061 0.2604 0. 6334

Strongest 0.3 0.4 0.3

Stronger 0.4 0.3 0.2

Strong 0.2 0.1 0.2

Weak 0.1 0.1 0.2

Weaker 0 0.1 0.1



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Table.7-Weights for Practical Training

Ck PRACTICAL TRAINING (0.6372)

Cij 0. 20087 0.07885 0.51941 0.20087

Strongest 0.3 0.4 0.3 0.3

Stronger 0.3 0.2 0.2 0.4

Strong 0.2 0.1 0.2 0.2

Weak 0.1 0.1 0.2 0.1

Weaker 0.1 0.1 0.1 0

Table.8-Weights for Exam Pattern

Ck EXAM PATTERN (0.2583)

Cij 0.1042 0.6372 0.2583

Strongest 0.4 0.2 0.4

Stronger 0.2 0.4 0.2

Strong 0.1 0.3 0.1

Weak 0.2 0.1 0.1

Weaker 0.1 0 0.2



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The above digitals can be used to investigate,

B1= (0.1061 0.2064 0.6334)

B1 = (0.3044 0.2310 0.1685 0.1579 0.0840)

Similarly, we can get

B2 = (0.3079 0.2603 0.1921 0.1519 0.0799), and

B3 = (0.2724 0.3274 0.2274 0.1104 0.0621)

So, B = Uk .

OR

= (0.1042 0.6372 0.2583).

B = (0.2983 0.2745 0.1987 0.1418 0.0757)

If V= (2,1,0,-1,-2), then the result will be

KML1 = (0.2983 0.2745 0.1987 0.1418 0.0757). (2,1,0,-1,-2)

KML1 = 0.5779, where KM1.= Knowledge Management level of Ist college.

0.3 0.4 0.2 0.1 0

0.4 0.3 0.1 0.1 0.1

0.3 0.2 0.2 0.2 0.1

B1

B2

B3

0.3044 0.2310 0.1685 0.1579 0.0840

0.3079 0.2603 0.1921 0.1519 0.0799

0.2724 0.3274 0.2274 0.1104 0.0621



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Proceeding in the similar manner we can get KML2 = 0.1310 and KML3 = 0.6995.

The above result shows that KM level of third educational institution is best among all the three

institutions.

VII. CONCLUSIONS

Today, colleges play an important role in shaping the future of the country, so the evaluation of

their knowledge management level is of great significance. In this paper, we have used the

Analytical Hierarchy process combined with Fuzzy Comprehensive Evaluation Technique to

evaluate the level of knowledge management for Educational Institutions which seems to be

worthwhile in taking such a type of decisions, as it gives the results in the form of numerical

quantities which is very helpful in understanding the underlying problem. From this research

work we can conclude that the average knowledge management level of the Educational

Institutions is still very low and there is a strong need of taking corrective actions in this

direction.

REFERENCES

1 Heung-Suk Hwang, Chiung Moon, Chun-Ling Chuang and Meng-Jong Goan3 (2005).

Supplier Selection and Planning Model Using AHP. International Journal of the

Information Systems for Logistics and Management (IJISLM), Vol. 1, No. 1, pp. 47-53

(2005)

2 Jay Liebowitz (2005) Linking Social Network Analysis with the Analytic Hierarchy

Process for Knowledge Mapping in Organizations Journal Of Knowledge Management

Vol. 9 NO. 1 2005, pp. 76-86, Q Emerald Group Publishing Limited, ISSN 1367-3270

3 Kamal M. Al-Subhi Al-Harbi (2001). Application of the AHP in Project Management.

International Journal of Project Management 19 (2001)

4 Maryam Alavi and Dorothy E. Leidner (1999). Knowledge Management Systems: Issues,

Challenges, and Benefits. Association for Information Systems.



www.gjmr.org

164

5 NIU Dongxiao, LI Jianqing (2010), Evaluation on the Level of generation Enterprise

Knowledge Management Based on AHP and Gray Relational Analysis. IEEE

International Conference.

6 Qian-Wang Deng, Yong-Zheng Tian (2008). Modeling Knowledge Management

Processes from Perspectives of Knowledge Agents. IEEE International Conference.

7 Rizwana Irfan, Maqbool uddin-Shaikh (2010). Enhanced Knowledge Management

Process for Group Decision Making. Second IEEE International Conference on Future

Information Technology and Management Engineering.

8 Robert G. and Eure, P.E (2009). Knowledge Management As an Integral Component of

Systems Engineering .Incose International Council of System Engineering.

9 Thomas L. Saaty (2008). Decision Making with the Analytic Hierarchy Process. Int. J.

Services Sciences, Vol. 1, No. 1, 2008.

10 Yang Tong (2009) Summary Research of Risk Identification in the Process of Knowledge

Management. Second IEEE International Conference on Future Information Technology

and Management Engineering.

11 Ting Wang and Lifeng Li (2010). A New Hybrid Method to Evaluate the HPR

Performance Based on FCE and AHP. Third IEEE, Computer society’s International

Conference on Knowledge Discovery and Data Mining.



EVALUATION OF KNOWLEDGE MANAGEMENT LEVEL OF

EDUCATIONAL INSTITUTIONS USING ANALYTICAL HIERARCHY

PROCESS: A CASE STUDY IN INDIA

Mohit Maheshwarkar*

N. Sohani, **

Pallvai Maheshwarkar***

ABSTRACT




or embedded in organizational processes or practice. Today many enterprises’ main profit

gradually relies on the innovation, which should be established on the knowledge management

system. However, the cost of executing the project of knowledge management is always high, and

to build up a set of effective criterion to realize the achievement of the project is significant. This

research bases on the key success factors of the KM project and applies to the Analytical

Hierarchy Process (AHP) to calculate the level of Knowledge Management for Educational

Institutions in an Indian city, Indore.

Keywords: Knowledge Management, Analytical Hierarchy Process.

*Assist. Professor, R.I.T, Indore (M.P)

** Reader ,I.E.T, D.A.V.V. , Indore (M.P)

***Assist. Professor, P.I.T.S, Ujjain (M.P)



I. INTRODUCTION




or embedded in organizational processes or practice. Knowledge management is a management

whose core is knowledge, and a series of process management that is collections, organization,

innovation, diffusion, use and development of knowledge on which production and operation of

enterprises relies. It is a management philosophy and methods, through the systematic use of

information content, processes and expert skills; it can improve the innovative capability of

enterprises and rapid response capability. Knowledge management is a process. The content of

knowledge management includes the contents of a system, not only referring only to a particular

aspect. The main content of knowledge management should include four parts: knowledge

acquisition, knowledge management systems, knowledge sharing, and knowledge utilization.

These four sections are closely connected, interdependent and mutually reinforcing. Educational

Institutions face huge competition. Due to the introduction of competition in the market in Indian

, these Educational Institutions face unprecedented challenges. Therefore, KM is of extreme

importance to these institutions.

II. EVALUATION OF EDUCATIONAL INSTITUTIONS’ KNOWLEDGE

MANAGEMENT LEVEL

Knowledge management underlines the learning and inheritance of human knowledge, and

emphasize on creation, accumulation, use and updates of internal knowledge. Through the

implementation of knowledge management, colleges can update and manage their knowledge

innovation to create favorable conditions and environment, and can achieve the best combination

and effective use of the knowledge of their faculty members .Therefore, the introduction of

knowledge management theory to these institutions is the only way to survival and development.

To gain a leading edge in the competition, colleges faced with the primary task is to enhance the

ability of individual faculty members. Through the strengthening and aggregation of individual

capacities, we can improve the overall organization's ability to win competitive advantage in the

management, knowledge and talent areas. The Educational Institutions perform a difficult task of

handling the future of the country.They provide services which lead and represent the nation at



the global level. The evaluation of level of knowledge management is the important work which

should be considered as a primary task from educatioal point of view for the country.In the

evaluation the level of a college’s knowledge management, the objective has great significance

for the development of facilities provided to the students. For this purpose we follow the

principles of scientific, systematic, hierarchical nature, practicality and operability.

III. ANALYTICAL HIERARCHY PROCESS

The Analytic Hierarchy Process (AHP) is a structured technique for helping people deal with

complex decisions. Rather than prescribing a "correct" decision, the AHP helps people to

determine one. An AHP hierarchy is a structured means of describing the problem at hand. It

consists of an overall goal, a group of options or alternatives for reaching the goal, and a group

of factors or criteria that relate the alternatives to the goal. In most cases the criteria are further

broken down into sub criteria, sub-sub criteria, and so on, in as many levels as the problem

requires (Fig. 1).The hierarchy can be visualized as a diagram like the one below, with the goal

at the top, the alternatives at the bottom, and the criteria filling up the middle. In such diagrams,

each box is called a node. The boxes descending from any node are called its children. The node

from which a child node descends is called its parent. Applying these definitions to the diagram

below, the five Criteria are children of the Goal, and the Goal is the parent of each of the five

Criteria. Each Alternative is the child of each of the Criteria, and each Criterion is the parent of

three Alternatives.



Fig. 1 – Hierarchical Structure for AHP (Thomas L. Saaty, 2008)

Once the hierarchy is built, the decision makers systematically evaluate its various elements,

comparing them to one another in pairs. In making the comparisons, the decision makers can use

concrete data about the elements, or they can use their judgments about the elements' relative

meaning and importance. It is the essence of the AHP that human judgments, and not just the

underlying information, can be used in performing the evaluations. For this purpose a pair wise

comparison scale is used, which is shown in the Table.2 given below. After that AHP converts

the evaluations to numerical values that can be processed and compared over the entire range of

the problem. A numerical weight or priority is derived for each element of the hierarchy,

allowing diverse and often incommensurable elements to be compared to one another in a

rational and consistent way. Priorities are numbers associated with the nodes of the hierarchy.

The priority of the Goal is taken as 1.000. The priorities of the children of any Criterion can also

vary but will always add up to 1.000, as will those of their own children, and so on down the

hierarchy. If the priorities within every group of child nodes are equal then the priorities are

called Default Priorities. The priority of an attribute with respect to the ultimate goal is called

Global Priority. The priorities indicate the relative weights given to the items in a given group of

nodes. Depending on the problem at hand, "weight" can refer to importance, or preference, or

likelihood, or whatever factor is being considered by the participants. This capability

distinguishes the AHP from other decision making techniques. In the final step of the process,

numerical priorities are derived for each of the decision alternatives. Since these numbers

represent the alternatives' relative ability to achieve the decision goal, they allow a

straightforward consideration of the various courses of action.

Table 1 – Pair Wise Comparison Scale (Thomas L. Saaty, 2008)



Saaty (2008) developed the following steps for applying AHP:

i. Define the problem and determine its goal,

ii. Structure the hierarchy with the decision maker’s objective at the top with the

intermediate levels capturing criteria on which subsequent levels depend and the bottom

level containing the alternatives, and

iii. Construct the set of n× n pair wise comparison matrices for each to the lower levels with

one matrix for each element in the level immediately above. The pair wise comparisons

are made suing the relative measurement scale (as discussed above). The pair wise

comparisons capture a decision maker’s perception of which element dominates the

other.

iv. There are n(n-1)/2 judgments required to develop the set of matrices in step 3.

Reciprocals are automatically assigned in each pair wise comparison.

v. The hierarchy synthesis function is used to weight the eigenvectors by the weights of the

criteria and the sum is taken over all weighted eigenvector entries corresponding to those

in the next lower level of the hierarchy.

vi. After all the pair wise comparisons are completed, the consistency of the comparisons is

assessed by using the Eigen value, λ, to calculate a consistency index, CI:

CI = (λ-n)/ (n-1).

Where n is the matrix size. Judgment consistency can be checked by taking the

consistency ratio (CR) of CI with the appropriate value in table 2, given below. Saaty

[1980] suggests that the CR is acceptable if it does not exceed 0.10. If the CR is greater

than 0.10, the judgment matrix should be considered inconsistent. To obtain a consistent

matrix, the judgments should be reviewed and repeated.



Table.2- Average Random Consistency Index

Size of

Matrix 1 2 3 4 5 6 7 8 9 10

Random

Consistency 0.00 0.00 0.58 0.90 1.12 1.24 1.32 1.41 1.45 1.49

IV. LITRETURE REVIEW

Robert G. and Eure P.E (2009) tell that Knowledge needs to be managed by the enterprise as an

enterprise asset. They also focus on knowledge management. According to them Knowledge

management provides tools to achieve optimum effectiveness. They also insisted to include the

KM as a topic in the Systems Engineering Handbook. Rizwana Irfan and Maqbool uddin-Shaikh

(2010) find that data and knowledge coming from heterogeneous sources and formats are

required to be efficiently extracted, transformed and stored for decision making. Their proposal

provides qualitative approach for enhancing the existing conceptual model for knowledge

processing to do transformation.

NIU Dongxiao and LI Jianqing (2010) investigate that Knowledge management is a process to

improve the competitiveness of enterprises and identify the knowledge, acquire it and play its

full role in the process. Knowledge Management is a new tool in management studies and a

powerful tool for the development, use and sublimation of enterprise knowledge resources. They

conclude that if the power generation companies want to sustain competitive advantage in the

knowledge economy era, they should be started a developed corporate culture based on

knowledge management-oriented as soon as possible, so that the organization's innovative

capacity and creativity of staff's personal mutually promote and make common progress. Qian-

Wang Deng and Yong-Zheng Tian (2008) used an approach of integrating knowledge

management process models into product development process models. In the approach, a

method named knowledge-based engineering process model is adopted as the method of

modeling a product development process. To realize the integration between knowledge

management process model sand the product development process models, a basic rule,

considering the knowledge management process as a special kind of sub-process in product



development processes, is followed. Maryam Alavi and Dorothy E. Leidner (1999) focus on

achieving the correct amount and type of accurate knowledge and garnering support for

contributing to the Knowledge Management System (KMS). Yang Tong (2009) classifies and

concludes the risks existed in knowledge management from a view of identification. The

research has been divided into following aspects of knowledge assets at risk: the risk of

knowledge spillovers, knowledge conversion risk, the risk of wastage, leakage risks, contractual

risks, moral hazard from Knowledge and knowledge of risk vector.

Thomas L. Saaty (2008) tells that the Analytic Hierarchy Process (AHP) is a theory of

measurement through pair wise comparisons and relies on the judgments of experts to derive

priority scales. It is these scales that measure intangibles in relative terms. The comparisons are

made using a scale of absolute judgments that represents how much more; one element

dominates another with respect to a given attribute. The judgments may be inconsistent, and how

to measure inconsistency and improve the judgments, when possible to obtain better consistency

is a concern of the AHP. The derived priority scales are synthesized by multiplying them by the

priority of their parent nodes and adding for all such nodes. He also tells that Analytic Hierarchy

Process (AHP) is a theory of relative measurement with absolute scales of both tangible and

intangible criteria based on the judgment of knowledgeable and expert people. How to measure

intangibles is the main concern of the mathematics of the AHP. The AHP reduces a

multidimensional problem into a one dimensional one. Decisions are determined by a single

number for the best outcome or by a vector of priorities that gives an ordering of the different

possible outcomes. We can also combine our judgments or our final choices obtained from a

group when we wish to cooperate to agree on a single outcome.

Jay Liebowitz (2005) discusses about the novel approach in applying the analytic hierarchy

process (AHP) to generate the ratio scores for the valued graphs to be used in Social Network

Analysis (SNA) in order to develop a knowledge map of the organization. According to him it

quantifies subjective judgments used in decision-making, and has been applied in numerous

applications throughout the world. Kamal M. Al-Subhi and Al-Harbi (2001) tell that the

Analytical Hierarchy Process (AHP) as a potential decision making method for use in project

management. They used contractor prequalification problem as an example. For this a

hierarchical structure is constructed for the prequalification criteria and the contractors wishing

to prequalify for a project. They found that by applying the AHP, the prequalification criteria can



be prioritized and a descending-order list of contractors can be made in order to select the best

contractors to perform the project. Their paper presents group decision-making using the AHP.

Heung-Suk Hwang et al. (2005) used a supplier selection analysis model with the help of AHP

method.

V. CASE STUDY

In this paper we test the knowledge management level of colleges’ on the anvil of different

criteria. The selected evaluationa criteria are : Conceptual Teaching, Practical Assessment,

Expert Lecture Criteria, Educational Visits and Problem Sorting. This evaluation criterion

has been developed on the basis of literature review and a series of informal discussions with a

large number of academicians. On these selected criteria different Educational Institutions will

be tested. Here the Educational Institutions selected for the analysis are three in nos. Fig.2

shows the hierarchical structure.

Fig.2 – Hierarchical Structrue for Knowledge Management Level Evaluation

A. Comparison of Criterion

On making pairwise comparisons of all the five criterias we will get the following combinations.

Conceptual Teaching Vs. Practical Assessment

Conceptual Teaching Vs. Expert Lecture Criteria

Conceptual Teaching Vs. Educational Visits

Conceptual Teaching Vs. Problem Sorting

Practical Assessment Vs. Expert Lecture Criteria

Practical Assessment Vs. Educational Visits



Practical Assessment Vs. Problem Sorting

Expert Lecture Criteria Vs. Educational Visits

Expert Lecture Criteria Vs. Problem Sorting

Educational Visits Vs. Problem Sorting

As a result of these pair wise comparisons we will get the following pairwise comparison matrix:

Table.3- Pairwise Comparison Matrix for different criteria

From/To Conceptual

Teaching

Practical

Assessment

Expert

Lecture

Criteria

Educational

Visits

Problem

Sorting

Conceptual

Teaching 1 1 5 3 4

Practical

Assessment 1 1 1 4 4

Expert Lecture

Criteria 1/5 1 1 4 5

Educational

Visits 1/3 1/4 1/4 1 5

Problem Sorting 1/4 1/4 1/5 1/5 1

On solving the above matrix analytically or simply putting the values in AHP software we will

get the following results:



Table.4- Priority values for different criteria

S.No Criteria Priority

1. Conceptual Teaching 0.3545

2. Practical Assessment 0.263

3. Expert Lecture Criteria 0.21656

4. Educational Visits 0.1139

5. Problem Sorting 0.05142

C.I. = 0.070911, R.I. = 1.12, C.R. = 0.0625<0.10

B. Comparion of Institutions

Now the priorities for the Educational Institutions were calculated. For the purpose of

comparison of evaluation of level of conceptual teaching, syatametically disigned quesitonnire

was given to the students and the results were plotted on a pairwise comparison matrix, given as

follows:

Table.5- Pairwise comparison matrix for Conceptual Teaching Criteria

From/To A B C

A 1 1/3 1/5

B 3 1 1/3

C 5 3 1

On solving the above matrix we will get the following priority values:



Table.6- priority values for Conceptual Teaching Criteria

COLLEGES PRIORITIES (LOCAL) PRIORITIES (GLOBAL)

A 0.106 0.037577

B 0.2604 0.09231

C 0.633345 0.22452

C.I.= 0.0192555, R.I.=0.58, C.R.=0.033<0.10

Proceeding in the similar manner we will get the different priority matrices and different values

of priorities for different criteria. The details of matrices along with the results are given as

follows:

Table.7- Pairwise comparison matrix for Practical Assessment Criteria

From/To A B C

A 1 5 6

B 1/5 1 3

C 1/6 1/3 1

Table.8- priority values for Practical Assessment Criteria


A 0.70708 0.1859

B 0.20141 0.05297

C 0.0915 0.0240

C.I. =0.0470076, R.I.=0.58, C.R.=0.0810<0.10



Table.9- Pairwise Comparison for Expert Lecture Criteria

From/To A B C

A 1 1/4 2

B 4 1 5

C 1/2 1/5 1

Table.10- Priority values for Expert Lecture Criteria


A 0.2014 0.043615

B 0.6806 0.147390

C 0.1179 0.025532

C.I. =0.0122975, R.I. =0.58, C.R. = 0.0210<0.10

Table.11- Pairwise Comparison for Educational Visits Criteria

From/To A B C

A 1 4 8

B 1/4 1 5

C 1/8 1/5 1

Table.12- Priority values for Educational Visits Criteria


A 0.6893 0.07851

B 0.2437 0.02775

C 0.0666 0.00758

C.I. =0.0470076, R.I. =0.58, C.R. = 0.0810<0.10



Table.13- Pairwise comparison matrix for Problem Sorting Criteria

From/To A B C

A 1 3 9

B 1/3 1 7

C 1/9 1/7 1

Table.14 – Priority values for Problem Sorting Criteria


A 0.6486 0.03335

B 0.2946 0.015148

C 0.0567 0.00291

C.I. =0.0401499, R.I. =0.58, C.R. =0.0692<0.10

Finally, on adding up the priority values for different criteria we will get the value of knowledge

management level for an institution.

Table.15- Comprehensive Evaluation of Educational Institutions

Evaluation of Knowledge Management Level – An AHP Approach

COLLEGES /CRITERIA Conceptual

Teaching

Practical

Assessment

Expert Lecture

Criteria

Educational

Visits

Problem

Sorting TOTAL

A 0.037577 0.1859 0.043615 0.07851 0.03335 0.378952

B 0.09231 0.05297 0.147390 0.02775 0.015148 0.335568

C 0.22452 0.0240 0.025532 0.00758 0.00291 0.284542

TOTAL 0.3545 0.263 0.21656 0.1139 0.05142 1.00000

11..000000000000



According to the evaluation system, the grades of "very high”, "Medium" and "low", are set

respectively. On this basis the colleges' are evaluated.

Table.16- Evaluation of Knowledge management level

S.No College Knowledge Management Level

1. A Very High

2. B Medium

3. C Low

VI. CONCLUSIONS

Today, colleges play an important role in shaping the future of the country, So the evaluation of

their knowledge management level is of great significance. In this paper, we have used the

Analytical Hierarchy process to evaluate the level of knowledge management for Educational

Institutions which seems to be worthwhile in taking such a type of decisions, as it gives the

results in the form of numerical quantities which is very helpful in understanding the underlying

problem. From this research work we can conclude that the average knowledge management

level of the Educational Institutions is still very low and there is a strong need of taking

corrective actions in this direction.

REFERENCES

1 Heung-Suk Hwang, Chiung Moon, Chun-Ling Chuang and Meng-Jong Goan3 (2005).

Supplier Selection and Planning Model Using AHP. International Journal of the

Information Systems for Logistics and Management (IJISLM), Vol. 1, No. 1, pp. 47-53

(2005)



2 Jay Liebowitz (2005) Linking Social Network Analysis with the Analytic Hierarchy

Process for Knowledge Mapping in Organizations Journal Of Knowledge Management

Vol. 9 NO. 1 2005, pp. 76-86, Q Emerald Group Publishing Limited, ISSN 1367-3270

3 Kamal M. Al-Subhi Al-Harbi (2001). Application of the AHP in Project Management.

International Journal of Project Management 19 (2001)

4 Maryam Alavi and Dorothy E. Leidner (1999). Knowledge Management Systems: Issues,

Challenges, and Benefits. Association for Information Systems.

5 NIU Dongxiao, LI Jianqing (2010), Evaluation on the Level of generation Enterprise

Knowledge Management Based on AHP and Gray Relational Analysis. IEEE

International Conference.

6 Qian-Wang Deng, Yong-Zheng Tian (2008). Modeling Knowledge Management

Processes from Perspectives of Knowledge Agents. IEEE International Conference.

7 Rizwana Irfan, Maqbool uddin-Shaikh (2010). Enhanced Knowledge Management

Process for Group Decision Making. Second IEEE International Conference on Future

Information Technology and Management Engineering.

8 Robert G. and Eure, P.E (2009). Knowledge Management As an Integral Component of

Systems Engineering .Incose International Council of System Engineering.

9 Thomas L. Saaty(2008). Decision Making with the Analytic Hierarchy Process. Int. J.

Services Sciences, Vol. 1, No. 1, 2008.

10 Yang Tong (2009) Summary Research of Risk Identification in the Process of Knowledge

Management. Second IEEE International Conference on Future Information Technology

and Management Engineering.



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PROBE FEED RECTANGULAR PATCH MICROSTRIP ANTENNA:

CAD METHODOLOGY

Dr. R.D. Kanphade*

Dr. D.G. Wakade**

Prof. N.T. Markad***

ABSTRACT

Antenna is a means for radiating or receiving radio waves. In addition to receiving or transmitting energy, an antenna is used in an advanced wireless system is usually required to optimize the radiation energy in same direction and suppress it in others. A micro strip patch antenna also referred to as patch antenna is a narrowband, wide beam antenna fabricated by etching the antenna element patch in metal trace bonded to an insulating dielectric substrate with a continuous metal layer bonded to opposite side of substrate which forms a ground plane. Probe feed rectangular patch Micro strip antenna simulated in FDTD software IE3D. Proposed novel probe feed rectangular patch microstrip antenna is presented. It has a return loss of -23.5dBat a frequency of 1.88GHZ. Antenna offers VSWR 1.15at a frequency of 1.88GHZ. Antenna offers a band width of 14 MHZ. By observing a smith chart it is seen that antenna offers resistive, capacitive and inductive impedance. Antenna offers unidirectional radiation pattern. Unidirectional radiation pattern plays important role in next generation mobile communication and computing Due to unidirectional radiation pattern cost of power of a mobile communication system is reduced. Probe feed rectangular patch micro strip antenna offer an antenna efficiency of 87%. Also antenna offers radiation efficiency of 86%. The exact location of the probe which can guarantee the desired performance is not given in the literature. So, hit and trial method is used to locate the co-ordinates of the probe feed which can provide satisfactory output. Using hit and trial, the co-ordinates of the probe were found to be (x, y) =(6,2).

KEYWORDS: Probe feed, Micro strip patch antenna, Efficiency, Radiation efficiency, VSWR,

Smith chart.

*Principal,Dhole Patil College of Engineering,Wagholi,Pune

**Director,P.R.Patil College of Engineering,Amravati

***Associate Professor,BVCOE,Deptt. Of ECE



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[I] INTRODUCTION

In telecommunication; there are several types of micro strip antennas( also known as printed

antennas) the most common of which is the micro strip patch antenna or patch antenna. A patch

antenna is a narrowband, wide-beam antenna fabricated by etching the antenna element pattern

in metal bonded to an insulating dielectric substrate with a continuous metal layer bonded to the

opposite side of the substrate which forms a ground plane. Common micro strip antenna

radiator shapes are square, rectangular, circular and elliptical but any continuous shape is

possible. Some patch antennas eschew a dielectric substrate and suspend a metal patch in air

above a ground plane using dielectric spacers, the resulting structure is less robust but provides

better band width. Because such antennas have a very low profile; are mechanically rugged and

can be conformable, they are often mounted on the exterior of aircraft and spacecraft or are

incorporated into mobile radio communication devices; [1].

Micro strip antennas are also relatively inexpensive to manufacture and design because of the

simple two dimensional physical geometry. They are usually employed at UHF and higher

frequencies because the size of the antenna is directly tied to the wavelength at the resonance

frequency [2].

A single patch antenna provides a maximum directive gain of around -6 dBi. It is relatively easy

to print on array of patches on a single (large) substrate using lithographic techniques. Patch

arrays can provide much higher gain than a single patch at little additional cost; matching and

phase adjustment can be performed with printed micro strip feed structures, again in the some

operation that form the radiating patches. The ability to create high gain arrays in a low profile

antenna is one reason that patch arrays are common on [3] airplanes and in other military

application. An array antenna is a special arrangement of basic antenna components involving

new factors and concepts. Before you begin studying about arrays, you need to study some new

terminology [4].

An array antenna is made up of more than one ELEMENT, but the basic elements is generally

the dipole. Sometimes the basic element is made longer or shorter than a half-wave, but the

deviation usually is not great [4] [5]. Typically an antenna is tuned for a specific frequency and is

effective for a range of frequencies that are usually on that resonant frequency. Some antenna



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design have multiple resonant frequencies, and some are relatively effective over very broad

range of frequencies. [6]

Gain as a parameter measures the efficiency of a given antenna with respect to a given norm,

usually achieved by modification of its directionality. An antenna with a low gain emits

radiation with about the same power in all directions, whereas high gain antenna will radiate in

particular direction. The radiation pattern of an antenna is the geometric pattern of the relative

field strengths of field emitted by the antenna. In field of antenna the term “radiation pattern”

most commonly refers to directional (angular) dependence of radiation from the antenna or other

source. Usually, the directivity is expressed in dBi. The reason that the units are dBi, (decibel

relative to an isotropic radiations that for n isotropic radiator, the radiated lower density is a

constant and therefore equals the average radiated power density ( the denominator). The angle

across the main lobe of an antenna pattern, between the two directions, at which, the antenna’s

sensitivity is half its maximum value at the centre of the lobe. It is abbreviated as HPBW[7][8].

As an electromagnetic wave travels through the different parts of the antenna system (radio, feed

line, antenna, free space) it may encounter differences in impendence (E/H; V/I, etc.) At each

interface, depending on the impedance match, some fraction of the wave’s energy will reflected

back to the source [5], forming a standing wave in the feed line. The ratio of maximum power to

minimum power in the wave can be ratio (SWR). A SWR of 1:1 is ideal. A SWR of 1.5:1 is

considered to be marginally acceptable in low power application. Efficiency is the ratio of

power actually radiated to the power put into antenna terminals. The bandwidth of an antenna

is the range of frequencies over which it is effective, usually centered on the resonant frequency.

The band width of antenna may be increased by several techniques, including using thicker

wires, replacing wires with cages to simulate a thicker wire, tapering antenna components (like

in a feed horn); and combining multiple antenna into a single assembly and allowing the natural

impedance to select correct antenna, small antenna are usually preferred for convenience, but

there is a fundamental limit relating bandwidth, size and efficiency. The polarization of an

antenna is the orientation of the electric field (E-plane) of the radios waves with respect to the

Earth’s surface and is determined by physical structure of the antenna and by its orientation. It

has nothing in common with antenna directionality terms: horizontal, vertical and circular (9)

[10]



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In high performance aircraft, satellite and missile applications, where size, weight, cost,

performance, ease of installation and aerodynamic profile are constraints, and low profile

antenna may be required. To meet there requirement microstrip antenna can be used. These

antennas are low profile, conformable to planar and non-planar surfaces. Simple and

inexpensive to manufacture using modern printed-circuit technology. Mechanically robust when

mounted on rigid surfaces compatible with MMIC design [11].

There are many configurations that can be used to feed micro strip antenna. The four most

popular are :-

Microstrip line

Coaxial cable

Aperture coupling

Proximity coupling

The micro strip line feed is easy to fabricate; simple to match by controlling the inset position

and rather simple to model. Because the dimensions of the patch re finite along the length and

width; the fields at the edges of the patch undergo fringing. The amount of fringing is a function

of the dimensions of the patch and the height of the substrate. Due to fringing field antenna

radiate. Fringing Fields Shown in Figure 1.

Figure 1 Fringing Field Figure 2 Patch Antenna



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[II] FEED NETWORK

Feed is of different types but most popular feed are –

Transformer feed

Microstrip line feed

Coaxial cable feed

Aperture coupling feed

Proximity coupling feed.

Out of above mentioned feed for micro strip patch antenna feed applied to it is transformer feed

type. Suppose impendence at antenna is 100Ω by transformer type feed 100Ω . This 50Ω

impendence known as terminating impendence. Terminating impendence matches to probe

impedance hence power delivered to micro strip patch antenna is maximum. [11]

The exact location of the probe which can guarantee the desired performance is not given in the

literature. So, hit and trial method is used to locate the co-ordinates of probe feed which can

provide satisfactory output. Using hit and trial, the co-ordinates of the probe were found to be

(x,y) =(6,2).

[III] DESIGN OF RECTANGULAR PATCH ANTENNA WITH PROBE FEED.

The three essential parameters for the design of a rectangular patch antenna are:- The resonant

frequency of the antenna must be selected appropriately. The personal communication system

(PCS) uses the frequency range from 1850-1990 MHZ. Hence the antenna design must be able

to operate in this frequency range. The resonant frequency selected for our design is 1.9 GHZ.

The dielectric material selected for our design is FR4 which has a dielectric constant of 4.4. A

substrate with a high dielectric constant has been selected since it reduces the dimensions of the

antenna.

For the micro strip patch antenna to be used in cellular phones, it is essential that the antenna is

not bulky. Hence, the height of the dielectric substrate is selected as 1.6mm.

Calculation of width (W) :- The width of the micro strip patch antenna is given by :



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W = C____________

2f0√(Єr+1/2)

Substituting C=3e8m/s ; Єr= 4.4 and f0 = 1.9GHZ

We get W = 0.048 m = 48.0mm

Calculation of Effective dielectric constant (Єreff) :-

The effective dielectric constant is calculated as : Єreff = (Єr+1)/(Єr-1)/2[1+12h/w]-1/2

Substituting Єr =4.4; w= 48.0mm and h=1.6mm we get Єreff =4.14

Calculation of the Effective length (Leff) :- The effective length is given as Leff = C/(2

f0√Єreff).

Substituting Є reff=4.14,c=3e8m/s and f0=1.9 GHz.

Weget : Leff = 0.0388m = 38.8mm

Calculation of the length extension (∆ L):- The length extension is given as :

Substituting the values, we get; ∆ L=.412h(Єreff+ .3)( w/h+.264)/(Єreff.-.258)(w/h+.8)

Calculation of actual length of patch (L):-

The actual length is obtained by:

L= (Leff .– 2∆L )

Substituting the values, we get:

L= 37.3mm

In general, top view of probe, Feed rectangular patch micro strip antenna is shown in Fig.2.

Geometry probe feed patch antenna shown in Figure.2.

[IV] RESULTS AND ANALYSIS



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The design analysis gave the following results. Radiation pattern of probe feed rectangular patch

micro strip antenna is shown in Figure.3. The radiation pattern of probe feed rectangular patch

micro strip antenna is unidirectional. This unidirectional radiation pattern plays important role in

next generation mobile communication and computing. Due to unidirectional radiation pattern

cost of power of mobile communication is reduced.

Gain v/s frequency plot of probe feed rectangular patch micro strip antenna is shown in Figure.4.

From this plot, it is seen that antenna offers return loss of -23.5 dB at a frequency of 1.88 GHZ.

VSWR V/S frequency plot shown in Figure 5, From Figure 5 it is seen that antenna has a VSWR

of 1.15 at a frequency of 1.88 GHZ. Smith chart shown in Figure 6. From smith chart it is seen

that antenna offered resistive, capacitive as well as inductive impendence. Figure. 7 shows

efficiency v/s frequency plot. From this plot it is seen that probe feed rectangular patch micro

strip antenna offered antenna efficiency of 87% and radiation efficiency of 86%.



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Figure 3 RADIATION PARTTREN Figure 4 RETURN LOSS

Figure 5 VSWR Figure 6 EFFICIENCY



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[V] CONCLSION

It is seen that the design adopted for the probe feed rectangular micro strip patch antenna are

accurate. This antenna can be used at 1.88 GHZ frequency for mobile communication and

computing applications where the frequency of operation is 1.88 GHZ.

For antenna to work properly the VSWR must be less than two and return loss must be less than

10dB, only then the antenna will radiate or receive the power with minimum reflection. As

designed antenna has a return loss -23.5dB and VSWR 1.15 at a frequency of 1.88 GHZ, so this

antenna is used in mobile communication and computing satisfactorily. Probe feed rectangular

micro strip antenna are ideal for mobile communication, application where weight is the main

constraint. Due to unidirectional radiational pattern antenna plays important role in next

generation mobile communication and computing. Cost of power of mobile communication

system is saved due to this antenna.

[VI] REFERENCES

[1] Y Li, C. Chen, Y.cho “ A unified optimization Framework for microelectronics Industry”

Department of communication Engineering, national chiao Tung university, Taiwan

Figure 7 SMITH CHART



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[2] Tang, W.chow, Y,many microstrip line Discontinuities on one General Field – Based circuit

model, city university of Hon Kong, china University of waterloo, Canada.

[3] Caver K, and Mink J,. Micro strip Antenna Technology, IEEE, Transactions on Antenna and

propagation, vol.29, No. 1, January 1981.

[4] D.N. Schaubert, “Micro strip antennas, “ Electromagnetic, vil.12, pp.381-401, 1992.

[5] G.W. Garvin, R.E.Munson, L.T. Ostwald and K.G.Schroeder,” Low pro file electrically

small missile base mounted micro strip antenna,” in Dig int-syom... Antenna Propagation soc,

urbana, IL, June 1975, pp. 224-247.

[6] J.Q.Howell “Micro strip antennas” IEEE Trans Antenna propagation, vol. AP-23, No. 1,

pp.. 90-93, Jan 1975.

[7] I.R.J.Mailloux, J.Mcilvenna and N. Kernweis, “Micro strip array technology” IEEE

Trans. Antenna and propagation, vol.AP-29 No. 1, pp 25-38, Jan.1981.

[8] H.D.Weinschel, “Progress report on development of micro strip cylindrical arrays for

sounding rockets,” physic. And Sci. Lab, NEW Mexico state univ, LAS Cruces, 1973.

[9] J.R. James and G.J. Wilson, “New design techniques for microstrip antenna array” in

proc. 5th European Micro. Conf, Hamburg, Sept. 1975, pp. 102-106.

[10] Balanis, Antenna theory.

[11] R.D.Kanphade, D.G.Wakade and N.T.Markad “Micro strip patch antenna : computer

Aided Design Methology, International Journal of Electronics Communication Engineering,

Rohini, New Delhi, Octomber 2011.

[12] FDTD IE3D Reference Manual, Fremont : Zealand software Inc, 2006.

[16]K. Dessouky & 1. Ho, Propagation Results from the Sat el 1 i t e- l a Experiment , KAT-X

Quart er l y , JPL, No. 17, October 1988, pp7-12.



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[17]J. P. McCeehan and A. Bateman, Phase-locked transparent tone-in-band TTIB: A new

spectrum configuration particularly suited to the transmission of data over SSB mobile radio

networks, IEEE Trans on Conun~, Vol.COM-32, No.1, Jan. 1984, pp 81-87.

[18]A. Kanso, Novel Signal Processing Techniques for Pilot-Based SSB Mobile Radio Systems,

Ph.D Thesis, Dept. of Elec. Eng., Univ of Bath, Bath UK, 1985.

[19]A. Bateman and D.M. Haines, Direct Conversion Transceiver for Compact Low-Cost

Portable Mobile Radio Terminals, This conference Record.

[20]A. Baternan, R.J. Wilkinson and J.D.Marvi11, The Application of Digital Signal Processing

to Transmitter Linearisation, IEEE Eurocon 88, Stockholm, Sweden, 13'h-17th July 1988.

[21]C.R. Green, A.A. Lane, R. Shulka and P.N. Tombs,GaAs M

MICs for use in Phased Array Radar T/R Modules, IEE Colloquium on 'Electronically Scanned

Antennas, 21' January 1988, London, UK.756

[22]Advances in smart antenna system. Dr. D.G. Wakade and D.G. Rameshwer kawitkar SSGM

college of Engineering shegaon 444203 . received on 19th Jan 2005 accepted on 26th June 2005.

Journal of scientific and industrial research Vol.64, September 2005, PP 660- 665



DETERMINANTS OF GROWTH OF TOURISM INDUSTRY IN GOA: A

STUDY

Dr. Achut Pednekar*

ABSTRACT

Goa is known as the beach country of India. As per the projection made by the consultants,

around 1.6 million tourists are expected by the turnoff and with an expected average annual

growth rate of 6.36 per cent, the total traffic in the horizon year i.e. 2021 would increase to 3.2

million. The resultant growth in tourist traffic is infuse a heavy and steady to upgrade and

augment the present infrastructures, hence the study. A multiple regression coefficient has been

utilized to analyze the relationship between the arrival of tourists and the expenditure plan.

Apart from this, the trends of tourist’s arrivals as well as foreign charter flights have been

considered and analyzed with the help of percentage change method. Implications of the

research are that expenditure plan is not only the factors which are influencing the tourists in

Goa. Government of Goa should introduce and enhance new tourism and existing activities i.e.

adventure tourism, cultural heritage tourism, pilgrim tourism, business tourism, sports tourism,

and education and medical tourism. The existing facilities are not sufficient and should

channelize way to identify infrastructure and other developmental needs for tourism.

Keywords: Goa, Receipt, Capital, Expenditure Plan

*D.M’s College, Goa



INTRODUCTION

The World Tourism Organization (WTO) in its Tourism 2020 vision has estimated that there

would be about 1.0 billion total international tourists in all countries in the world in the year

2010 and 1.6 billion in 2020 compared to 0.57 billion in 1995. According to WTO estimates

Europe will continue to remain the most popular tourist destination with about 0.7 billion tourists

estimated for the year 2020. East Asia and Pacific region will surpass America by 2010 to

become the second most visited destination. International tourists in South Asia is expected at

0.2 billion in 2020 which is almost five times that of 1995 but still quite low compared to other

destinations. India is expected to fuel 4.5 times growth in international tourist’s arrival, between

1995 and 2020.

Goa has attracted 1.2 million of tourist traffic in the year 1997. As per the projection made by the

consultants, around 1.6 million tourists are expected by the turnoff and with an expected average

annual growth rate of 6.36 per cent, the total traffic in the horizon year i.e. 2021 would increase

to 3.2 million. It is projected that in 2021 domestic tourists would be 2 times the present level

and foreign tourist would be 4 times the present level and overall about 2.5 times.(Tourism

Master Plan : Goa 2011 Final Report February 2001)

The resultant growth in tourist traffic is infuse a heavy and steady to upgrade and augment the

present infrastructures. Therefore urgent efforts are required from the state to upgrade and

augment the present infrastructure stock to meet future requirement.

The Government of Goa has declared Tourism as an Industry with effect from 01/04/2000. The

Master Plan for tourism development upto 2011 A.D. has been prepared. The Tourism Policy of

the State has also been framed. Since a large multitude of the people in Goa are economically

dependent on tourism and related activities a decisive promotional thrust and reworking of the

appropriate tourism model have been identified as key elements in placing the potential of our

touristic state on a higher growth orbit. Tourism sector has been accorded the status of industry

entitling the hospitality sector to avail of benefits of concession available on water and power

tariffs, relief in service tax, luxury tax on hotel rooms and sales tax on cooked foods as well as

non alcoholic beverages in restaurants. The tourism departmental has proposed some new

projects like development of the tourism jetty and parking lot at Panaji, Paryatan Bhavan at Patto

Panaji, beach safety management system in the form of up gradation of access of tourist



destination in the state, development of eco-tourism project for state of goa, capacity building

organization of workshops/seminars/training programmes etc for improvement of tourism

manpower. The above infrastructure development projects have been processed for central

financial assistance to the tune of Rs. 7182.66 lakh with state component of Rs. 961.34 lakh.

Since it is decided to utilize proposed land for golf course at betul for food and park auxiliary,

town and country planning department has been requested to suggest suitable site for setting up

of golf course in the state.

Development of infrastructure facilities, beautification of important tourist destinations,

improvement of roads in tourism circuit, appointment of more life guards and improvement of

different safety measures have been continuing in order to improve services to the tourists

visiting the state. Department of tourism has already entrusted the work to a competent

organization “M/s Drishthi special Response Service, Pvt Ltd, Mumbai”.

Special Tourist Security force named as Tourist Security Organisation is proposed to be

formulated in order to provide additional protection and guidance to the tourists visiting the state.

Goa Heritage Tourism Scheme has been formulated which is approved by the Government and is

being implemented. The objective of this scheme is to restore and maintain ancestral houses of

goa by giving financial assistance with subsidy to the interested parties. In order to promote eco-

tourism, the Forest Department has been idenfied as nodal agency.

TOURISM MARKETING AND PROMOTION

Tourism has become a highly competitive industry. The department of tourism has strengthened

its marketing strategy by envisaging various publicity measures viz organizing road shows,

advertising through print and electronic media, participating in various travels marts. The

department of tourism participated in travel related overseas events like, road show at Durban

and cape town in south Africa, Leisure-08 at Moscow, WTM-2008 at London and domestic

events in India, like TTF at Jamshedpur, TTF at Hyderabad, TT F at Ahmadabad, ITM at Jaipur,

Rajasthan, TTE at Chennai, Discovery India. The Department also organized Explore the

Incredible State in Mumbai in coordination with Goa Tourism Corporation, Goa. Some festivals

are organized at state level to attract the domestic as well as foreign tourists such as carnival,



Shigmotsav, Saraswat food festival, wine festival etc. Fund for organizing these festivals are

provided by Tourism Department in order to promote tourism.

REVIEW OF LITERATURE

The Consulting Engineering Services (I) Ltd. New Delhi in his Tourism Master Plan: Goa –

2011 Final Report February 2001 has carefully studied views expressed by the Goa Chamber

of Commerce & Industry. GCCI have stressed on creation of facilities in order to sustain growth

of tourism in Goa.

Abhinav K. Raina Director, Centre for Tourists and Heritage Research Dayanand College,

Ajmer in his presentation in the 3rd Bi-annual referred international journal held on 23/01/2011

topic entitle “Development of Health Tourism services – A Study” stated that there is a need

for a training in the field of medical facilities in order to further boost tourism industry.

Tourism in Goa: A perspective (Collection of Domestic Tourism Statistics for the State of

Goa) in their survey report highlighted that almost 42.05% of the domestic tourist and 43.2% of

foreign tourist rated local transport services as good, with 12.1% and 10.8% respectively, rating

it as poor. 14.32% of domestic and 12.9% foreign tourists, reported the accommodation units as

excellent while 10.57% of domestic and 6.7% foreign tourists rated it as poor. 36.79% foreign

tourists and 35.1% domestic tourists rated quality of entertainment facilities as excellent. Almost

40.71% of domestic tourists and 42.1% foreign tourists rated the tourist attractions in Goa as

“Very Good”. Almost 61.3% of domestic tourists and 59.8% of foreign tourists rated shopping

facilities as adequate.

RESEARCH OBJECTIVES

1. To study and analysis of trends of tourist arrivals in goa.

2. To study and analysis of trends of arrivals of foreign charter flights.

3. To ascertain the relationship between arrival of tourist with expenditure plan.

Hypothesis

There is a significant relationship between arrivals of tourist with revenue and capital outlay on

tourism. (Expenditure plan)




The study is based on secondary data conducted in the state of goa. Data is collected from Govt

of Goa Department of tourism. Secondary data also has been collected by referring to various

journals, published and unpublished texts, books, reports, newspapers and net.

Data analysis was carried out by using the statistical program packages SPSS. The other

statistical techniques used for data analysis is percentage change method.

In order to know the aforementioned hypothesis, expenditure plan and arrivals of tourists from

the period 2000-01 to 2010-11 has been considered.

I TREND ANALYSIS OF TOURIST ARRIVALS IN GOA

Growth of tourism in Goa has been phenomenal. Growth of tourism has led to economic growth,

improved infrastructure and quality of life. Construction boom has led to increased urbanization.

Changes in pattern of livelihood and socio cultural changes have also occurred. People from

different parts of the country has come and settled in Goa in search of livelihood. There is also a

large expatriate community who come to enjoy the beauty of the land of sun and sea. Rapid

changes in economy, society and culture have led to greater inclination among the people to earn

quick money along with increased Westernization and growth in consumerism.

Eco Tourism has been promoted to develop the Hinterland, so that people living in these areas

can reap the benefits of tourism. Express ways are envisaged in an effort to shorten distances

between either extremities of the State, and these expressways will be connected to the golden

quadrilateral. Beach-life safety programme implemented successfully is probably the first of its

kind project in the country.

Table – I Trends showing number of tourist arrivals in goa

Year Domestic Foreign Total % Change

1985 682545 92667 775212 -

1986 736548 97533 834081 7.6

1987 766846 94602 861448 3.3

1988 761859 93076 854935 -0.7

1989 771013 91430 862443 0.9

1990 776993 104330 881323 2.2

1991 756786 78281 835067 -5.6



1992 774568 121442 896010 7.3

1993 798576 170658 969234 8.2

1994 849404 210191 1059595 9.3

1995 878487 229218 1107705 4.5

1996 888914 237216 1126130 1.7

1997 928925 261673 1190598 5.7

1998 953212 275047 1228259 3.2

1999 960114 284298 1244412 1.3

2000 976804 291709 1268513 1.9

2001 1120242 260071 1380313 8.8

2002 1325296 271645 1596941 15.7

2003 1725140 314357 2039497 27 .7

2004 2085729 363230 2448959 20.1

2005 1965343 336803 2302146 -6.0

2006 2098654 380414 2479068 7.7

2007 2208986 388457 2597443 4.8

2008 2020416 351123 2371539 -8.7

2009 2127063 376640 2503703 5.5

Economic survey 2008-09



Figure – I Chart showing number of tourist arrivals in Goa

The share of domestic overnight visitors was 84.50% & foreign overnight visitors were 15.50%

in the total overnight visitors in the state. Total domestic tourist estimated was 18.99 lakh,

‐500000

0

500000

1000000

1500000

2000000

2500000

3000000

1985

1986

1987

1988

1989

1990

1991

1992

1993

1994

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

2007

2008

2009

DOMESTIC

FOREIGN

TOTAL

% CHANGE



foreign tourists 3.48 lakh, and total tourists 22.47 lakh. Estimated day tourists are 2.42 lakh and

total tourists & day tourists combined is estimated to 24.89 lakh.

During the years from 1990 to 1998, the share of foreign tourists as share of total tourists visiting

goa has considerably increased from 11.83 per cent in 1990 to 22.39 per cent in 1998. This is

significantly higher than the normal trend of about 3.37 per cent (1997) of foreign tourists

observed in India. In between the year 1991 has seen a drastic fall in the arrival of foreign

tourists which may be attributed to unstable socio-political situation in the country. As per the

Tourism Department, in the year 2008, 2020416 domestic tourists’ and 351123 foreign tourists,

whereas, in 2009, 2127063 domestic tourists and 376640 foreign visited Goa. As per Economic

Survey released by the Government, contribution of tourism is 33 percent of the total GDP.

The growth of tourist in Goa is due various reasons. Place of tourist interest are so numerous and

of varied nature that it is not easy to describe these places comprehensively. In general the tourist

spots of Goa are counted more like, Shrines, Forts, places of historical importance, springs, lakes

and birds, sanctuaries, religious centers, science spots, sea beaches, summer resorts, waterfalls

and wild lives etc. Goa has been one of the major tourist destinations in India for foreign visitors.

Its share is around 11 per cent of the total foreigners visiting the country.

II TREND ANALYSIS OF ARRIVALS OF FOREIGN CHARTER

FLIGHTS

Table –II Trends showing arrivals by foreign charter flights

Year Number of flights Passengers

2000-01 419 116992

2001-02 279 76410

2002-03 384 94350

2003-04 523 126255

2004-05 690 158993

2005-06 719 180310

2006-07 720 169836

2007-08 710 175951

2008-09 615 145428

IJRIME

Econom

Figure II

On accou

flow to t

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tourists from more than 25 different countries including UK, Germany, Sweden, Switzerland,

Finland, Russia, etc. About 39% of the tourists came from UK followed by Russia, Germany,

Finland and France.

III THE RELATIONSHIP BETWEEN ARRIVAL OF TOURIST WITH

EXPENDITURE PLAN

Data was tabulated in Microsoft Excel Sheet and the data edited, coded and verified for validity.

The data was analyzed using statistical package for social sciences software.

Table III showing the arrival of tourists and expenditure plan for the year 2000-01 to 2010-

11

year Tourist(y) Revenue(x1) Capital(x2)

2000-2001 1268513 2.2 4

2001-2002 1380313 5.3 7

2002-2003 1596941 13 6

2003-2004 2039497 7 0.0033

2004-2005 2448959 4.3 1

2005-2006 23021146 24 2

2006-2007 2479068 7.23 1

2007-2008 2597443 5 2

2008-2009 2020416 0.26 0

2009-2010 2127063 10 24

2010-2011 21123000 7.2 8

Source: Department of tourism, Govt. of Goa.

Note: Compilation of secondary data



Table IV: Pearson Correlations between tourist and capital

Variables tourist capital

tourist Pearson

Correlation 1 -0.158

Sig. (2-tailed) 0.644

N 11 11

capital Pearson

Correlation -0.158 1


N 11 11

The result of Table I shows that there is (- 0.158) negative insignificant correlation between the

tourist and capital.



Table V: Pearson Correlations between capital and revenue

Variables capital revenue

capital Pearson

Correlation 1 0.144


N 11 11

revenue Pearson

Correlation 0.144 1


N 11 11

The result of Table II shows that there is (+0.144) positive insignificant correlation between the

capital and revenue.

Table VI: Pearson Correlations between revenue and tourist

variables revenue Tourist



revenue Pearson

Correlation 1 0.174


N 11 11

tourist Pearson

Correlation 0.174 1


N 11 11

The result of Table III shows that there is (+0.174) positive insignificant correlation between the

tourist and revenue.

Table VII: Model Summary of the Regression of arrival of tourist and capital and revenue

Model R R Square

Adjusted R

Square

Std. Error of the

Estimate

1 0.254(a) 0.064 -0.170 481324.74843

1. Predictors: (Constant), revenue, capital

Table IX Multiple Regression Analysis of Expenditure plan Coefficient (a)

Variables

Unstandardized

Coefficients

Standardized

Coefficients

t Sig. B

Std.

Error Beta

(Constant) 1986566.0 249673. 7.957 0.000



16 080

capital -

12028.573

22294.2

41 -0.186 -0.540 0.604

revenue 13951.539

24015.3

97 0.201 0.581 0.577

Dependent Variable: tourist

As seen from the table, revenue and capital have determined only 06 percent of the variance of

tourist. In the regression model both are insignicant, capital and revenue are not the only factors

which are influencing the tourists in Goa. There are other factors responsible for which the study

has to be done.

CONCLUSION

Implications of the research are that capital and revenue are not the only factors which are

influencing the tourists in Goa. The various factors that have contributed to this rise in domestic

tourism in the country are: increased disposable income of the middle class; increased

urbanization and stress of living in cities and towns; increased ownership of cars, which is

making domestic tourism more attractive; especially among the upper-middle and middle

classes; improved employment benefits, such as the leave travel concession; development of

inexpensive mass transport and improved connections to various places of tourist interest;

increased number of cheap accommodations and resorts, greater advertising targeted at domestic

tourists both by the central and the state governments, as well as the tourist industry, and

increasing of time-sharing in holiday spent, among the middle class.

Government of Goa should introduce and enhance new tourism and existing activities i.e.

adventure tourism, cultural heritage tourism, pilgrim tourism, business tourism, sports tourism,

and education and health tourism. The existing facilities are not sufficient and should channelize

way to identify infrastructure and other development needs for tourism.

REFERENCES

Books



Batra G.S.and A.S Chawla (1995) Tourism Management: A Global Perspective, Deep and Deep

Publications, New Delhi.

Chawla R. (2005) Ecotourism Planning and Management, Sonali Publications, New Delhi.

Chawla R. (2006) Responsible Tourism, Sonali Publications, New Delhi.

Chawla R. (2006) Agri- Tourism, Sonali Publications, New Delhi.

Magazines

De Costa I. (2005) Need for a New Approach, Goa Today.

De Souza R. (2006) Boosting State Tourism, Goa Today.

De Costa I. (2005) Need for a New Approach, Goa Today.

Report

Tourist Statistics 2006-07, Department Of Tourism, Goa

Tourism Master Plan: Goa – 2011 Final Report February 2001

Websites log on 18-07-2011

http://www.hindu.com

http://www.goa-tourism.com

www.gdrc.org

www.ecoindia.com/sustainable-tourism

www.du.ac.in/coursematerial/ba/tourism/Lesson21-23

banglanatak dot com research report –Goa.pdf (application/pdfobject)

Websites log on 25-07-2011

http://tourism.visitcalifornia.com/Research/

www.mcos.com/Tourism_Industry.htm

www.mcos.com/Healthcare_Industry.htm

http://goacom.blogspot.com/2009/01/goa-beach-strip-of-paradise.html