71

CHAPTER 4

RESEARCH DESIGN AND METHODOLOGY

72

4. RESEARCH DESIGN AND METHODOLOGY

4.1 DESCRIPTION AND DEMOGRAPHIC DETAILS OF PIMPRI

CHINCHWAD MUNICIPAL CORPORATION (PCMC) AND PUNE

MUNICIPAL CORPORATION (PMC)

Overview of PCMC: In 1982 Pimpri Chinchwad Municipal Corporation was formed

and was mainly an Industrial hub. By 2001 the population started growing exponentially

for the residential sector too and the population increased from about six lakhs in 2001 to

16 lakhs in 2010-11. PCMC which developed as supporting township for Pune has now

made its own identity through the development of auto and auto ancillaries as well as IT

hubs coming up in Hinjewadi, Chakan, Talegaon. The vision of PCMC by 2008-09

aimed for not only economic development of the city but also for improvement of the life

of the citizen of PCMC. The identified vital areas included providing universal access of

municipal services to the urban poor, improvement in education standards and efficient

civic services.

The vision led towards aim for the development integrated e- governance program that

would result in improved transparency, efficiency which will simultaneously lead

towards the building citizen centric government. PCMC in 2010-11 has proposed to

deliver online services thereby reducing the footfalls in its offices. During the qualitative

study and after interviews with the PCMC employees it was found that the

implementation of e- governance was going on in two phases. Phase I comprised of

identification of the services of people interaction which had been completed. From 2010

Phase II started which dealt with bringing all the operational activities of different

departments on e- government platform and interlinking each of them for efficient

sharing of information and control. During the Phase I implementation the following

services were included in e- governance:

1. Property & Water Revenue Management

2. e- Procurement

3. Building Permission Management

4. Dashboard for Works Management

5. Grievances Management

6. Solid Waste Management with Vehicle Tracking

73

7. Online Death & Birth Certificate

This showed and evidenced that knowledge management for e- governance was in

nascent stage during my study and this is why the study continued with the qualitative as

well as quantitative study for Pune Municipal Corporation.

Pune Municipal Corporation Overview: Pune, the Oxford of the East is a historical

city in India with a glorious past, an innovative present and a promising future. Since

1950, the Pune Municipal Corporation is administrating the city and serving citizens.

Pune Municipal Corporation has taken an initiative for implementing e-Governance.

Success of e-governance depends on use of Information Technology in mobilization of

Government resources and utilization of these scarce resources with an aim of providing

a better service.

History: The Pune Municipal Corporation (PMC) was established on 15

February 1950. The PMC controls the whole administration of Pune. The

executive power of the corporation is vested in the Municipal Commissioner, an

Indian Administrative Service (IAS) officer appointed by the Maharashtra state

government. The corporation consists of directly elected corporators headed by a

Mayor. The mayor has few executive powers.

The PMC is in charge of the civic needs and infrastructure of the metropolis.

Pune is divided into forty-eight municipal wards, each represented by 3 members

and overseen by an Assistant Municipal Commissioner for administrative

purposes. The corporators of the administration are elected by the people through

a popular vote and almost all the state political parties participate in the election.

The city comes under the Haveli Taluka of Pune District, Maharashtra. The

collectors are in charge of property records and revenue collection for the Central

government. They also conduct national election in the city. Like other

metropolises in India, the Pune Police is headed by a Police Commissioner, an

Indian Police Service (IPS) officer. The Pune Police is the law enforcing agency

in the city and comes under the state Home Ministry.

The Pune Municipal Corporation is well known as Pune Mahanagar Palika and is

serving citizens since 1950. To Serve Citizens better Pune Municipal Corporation

has taken initiative for e-Governance. Presently a few big corporations like

Persistent Systems are lending help for developing the E-governance system, as a

74

part of their social service initiative. A public-private partnership is perceived to

bring tremendous changes in the future.

The Pune Municipal Corporation is planning to merge 15 new villages in its

jurisdiction. After the merger, the PMC's total area will increase to 552 km2 from

the existing 430 km2 (as mentioned on the PMC's website) making it the biggest

municipal corporation in the state as per area. The 15 villages include Mhalunge,

Sus, Bavdhan, Kirkatwadi, Pisoli, Lohegaon, Dhavade Kopare, Kondhwa

Dhavade, Nanded, Khadakwasla, Shivane, Hadapsar (Sadesatara Nali part),

Mundwa (Keshavnagar), Manjari, Narhe, Ambegaon, Dhayari, Uruli Kanchan

and Phursungi.

Pune Municipal Corporation was established on 15th February 1950 Population

(Year 2001) 3 Million Population of 38 Villages 3,05,281 Square Area 430 Sq.

km. Total Zones 48 PMC Members 151 Municipal Employees Class No. of

Employees 1 54 2 211 3 3,695 4 11,049 Total 15,054 Budget (2006-2007)

Municipal Markets 19 Municipal Gardens 57 Boating Clubs 2 Zoo 2 Aquarium 1

Snake Park 1 Swimming Pools 7 Fire Brigade Centers 8 Printing Press 1 Primary

Schools 315 Pre-Primary Schools 255 Total Students in Primary Schools Boys

61,414 Girls 62,125 Total 1,23,539 Total Students in Pre-Primary Schools Total

Students 10,200 Newly Added Students 750 Schools Higher Secondary Schools 5

High Schools 13 Total 18 Industrial Training Center 1 Technical High Schools 1

Total Students In High Schools Boys 7,674 Girls 7,386 Total 15,060 Total

Students In Industrial Schools Boys 177 Girls 50 Total 227 Dr.Ambedkar Hostel

Boys 152 PMC Hospitals 14 Clinics 40+1 Mobile Clinic Total Patients 3,350

Daily (Approx.) Number Of Slums 553 Declared Slums 347 Water Supply 650

Million liters/Day Water Drainage 150 Million liters/Day

Administration: The Pune Municipal Corporation (PMC) manages the city of

Pune. The major responsibility of PMC is to look after the civic and

infrastructural needs of the citizens of the Pune. The PMC is headed by a

Municipal Commissioner, who possesses the actual executive power. The

Municipal Commissioner is an officer of the Indian Administrative Service who

is appointed by the Government of Maharashtra.

The city of Pune is divided into 48 municipal wards (zones), represented by 3

members from each ward. The local administration of wards is mainly

75

administered by an Assistant Municipal Commissioner. The corporators of the

different wards are elected by the people through Municipal Elections which are

held quinquennially and in which local members of all major political parties

participate. The corporations are responsible for overseeing that their

constituencies have the basic civic infrastructure in place, and that there is no

lacuna on the part of the authorities. The corporation currently consists of 149

directly elected corporators, who are led by the Mayor of Pune. The Mayor of

Pune is a titular position with limited duties who acts as an ambassador and

representative of the city.

Mission of PMC: To provide faster, efficient, transparent and integrated on-line

IT Systems and Infrastructure Facilities to meet the service requirements of the

citizens and employees.

Objectives of PMC:

o Transparent & Accountable Citizen Services

o Improve Revenue collections by plugging of leakages

o Entry of data only once in the system and then use of it by other

departments

o Creation of a Decision Support System for better administration

o Reduce RTI queries by proactively sharing data with citizens

Objective of e- Governance at PMC:

o Improve the quality of Citizen Service Delivery mechanism and offer cost

effective services with optimal effectiveness and transparency.

o To create concurrent database and to allow data sharing across various

departments / ULBs/ Governments, thus bringing out effective

convergence process and thereby improve efficiency in day to day

functioning.

o Facilitate the decision making process at top management by availability

of the right information – anytime, anywhere.

o Help different departments to efficiently monitor revenue collection and

improve resource mobilization.

76

o Use of technology to implement citizen centric initiatives and enhance

governance through improved access to accurate information for

responsive management.

Existing IT Infrastructure at PMC: This includes servers, desktops, printers, latest

software, scanners, UPS, firewalls for protection, router, laptops, switches, RF Links

& Fiber (2Mbps), Leased Line for Internet (45Mbps), Video Conference facility

(PMC is connected to Collector office & MSWAN) which are contributing towards

the KM for e- governance.

Figure 4.1: Videoconferencing: A source of KM at PMC

Source: www.pmc.com

1. Implementation of m-Governance in PMC: Mobile Government can be defined as

a strategy and its implementation involving the utilization of all kinds of wireless and

mobile technology, services, applications and devices for improving benefits to the

parties involved in e-government including citizens, businesses and all government

units

o Currently mobile services used by

o property Tax

o Solid Waste Mgmt. Dept.

o

o

77

o

o

o

4.2 PROBLEM AREAS AND FUTURE PLANS

Many studies reveal that the efforts put-in the KM initiative goes down the drain and

the KM fails due to inability of the performing companies to resolve certain key issues.

A government institution seeking to adopt a KM model should consider some key

requirements. Most of the amount spent on the KM systems at higher levels is in loss

due to lack of proper guidance regarding the preparedness and implementation issues.

However, while the importance of the KM is recognized and interest is high, there is

also a great deal of confusion regarding, how effective KM strategies can be

developed. E-Governance is picking up pace day by day in our country which helps

citizen satisfaction which is the ultimate duty of the government. Survey of literature

reveals that there is a very meagre research done in this field and lots of potential is

there for research to be done in this area. The role played by the KM in e- governance

activities had to get examined at grass root level. Evaluation of the right variable for

designing a conceptual model is the need of the hour. The need is also to find a

method which can evaluate the different criterions of the KM processes & functions

for the e-Governance systems. There are problems as there are no standard methods or

model, no agreed upon metrics, not much research is done in this field, and who are the

right people in organization to evaluate the performance is also difficult to analyze

(details of survey of literature have been given in chapter-3). Keeping in view this gap

in research and its importance, the following problem has been undertaken for the

purpose of this study: “The Role of Knowledge Management for e- Governance in

a Public Service Organization with respect to Pune city”

4.3 TYPE OF RESEARCH

The research study started with the exploratory research where the researcher gained a

better understanding of the concept of Knowledge Management and e- Governance at

municipal corporation through the qualitative research, for this many experts of KM and

e- governance where interviewed through unstructured questions like the municipal

78

commissioner, additional Municipal commissioner, municipal commissioner of slum &

local body tax, HOD IT department of Pune Municipal Corporation. The study was

finally followed by conclusive research study where a well structured quantitative study

was conducted to test the promulgated hypothesis through a structured close ended

questionnaire.

4.4 OBJECTIVES AND HYPOTHESIS OF THE STUDY

Broadly, the present study has been undertaken to study and evaluate the role of

Knowledge Management for e-Governance in a public service organization.

4.4.1. OBJECTIVES OF THE STUDY

1. To study the role of Knowledge Management in e-Governance in a Public Service

Organization.

2. To design a general model or framework of Knowledge Management as a tool to

assist e-governance in a Public Service Organization.

3. To explore the factors affecting the success and hindrance in implementation

Knowledge Management in e-governance.

4.4.2. HYPOTHESIS OF THE STUDY

H1a: Practices of Knowledge Management in e-governance in a public service

organization (PMC) enhances performance of the organization.

H1b: Practices of Knowledge Management in e-governance in a public service

organization (PMC) enhances the productivity of the organization.

H2a: Practices of Knowledge Management in e-governance enhances the decision

making processes in a public service organization (PMC).

H2b: Practices of Knowledge Management in e-governance enhances fast decision

making processes in the public service organization (PMC).

79

4.5 UNIVERSE OF THE STUDY

For the purpose of the study, different Public Service Organizations located in

Pune were visited to have an overview and know the status of KM Systems applied for e-

governance activity. The Pune Municipal Corporation and PCMC were selected for the

study for the qualitative study. Out of which PMC was further selected for the final study

as it was bigger and had KM functions at backend for e- governance activities. After the

study it was found that there was a need to stratify the sample between class I and class II

employees since there is a demarcation of work between the two strata Class I is more

involved in planning, execution and supervision whereas class II employees are involved

in the implementation of services. Thus all the managers and executives working on KM

and e- governance activity were selected which formed the universe of this study.

4.6 SAMPLING FRAME

A public service organization from Pune region “Pune Municipal

Corporation” was selected for the purpose of the study. As the study is implied for a

public service organization Pune Municipal Corporation was selected for the qualitative

as well as quantitative study. Basis of the selection of this unit was the presence of

Knowledge Management & e- governance activity for a huge population and oldest

municipal corporation in Pune.

4.7 SAMPLE DESIGN

Stratified sampling method was used to design sample. From the selected

municipal corporation (Pune Municipal Corporation) respondents are identified in two

categories. Class I, Class II employees working on KM and Class I and Class II

employees working on e- governance systems were the respondents.

(A) Sample Plan for Knowledge Management for e- Governance:

For the smooth functioning of e- Governance in Municipal Corporation,

knowledge management acts as the backbone. For this PMC is maintaining the KM for e-

governance. PMC 465 class I & II executives as given on the PMC website which

constitute the sampling frame.

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The census was considered to collect data from class I officers who were working

on the KM in e- governance which counted to be 60 in number. However 22 class I

officers agreed to participate , whereas others denied due to due to time constraint and

their unwillingness to share information. Data was collected from 185 class II officers.

Equations for calculation of Sample Size: The minimum sample size required for the

study was calculated using the following equations (Yamane, 1967; Isreal, 1992), with

confidence level of 95%, e=5% or 0.05.

Equation 1: n = N

1 + N (e)2

Where:

N = Population

e = error allowed

n = Sample size

Equation 2: Finite Population Correction (FPC) was used to reduce sample size for

small populations (where sample size is greater then 5% of the population) by readjusting

with the following equation:

n = n0

1 + (n0 – 1)/N

Where:

n = Adjusted sample size

n0 = Sample size (Using equation 1)

N = Population

81

Sample Size Calculation: Using the equations 1 and 2 for calculation of sample size for

KM and e-governance, minimum sample size required for the study were 20 and 85

respectively. However for the purpose of the study from both class I & Class II officers

sample size was taken as 112. Detailed sample plan is given in Table 4.1

TABLE 4.1: SAMPLE PLAN (FOR RESPONDENTS)

Name of Public Sector Pune Municipal

Corporation

KM for e-Governance

(Class I Officers)

Universe 60

Sample 45

(at 5% confidence interval)

Data Collected 22

Knowledge

Management for e-

Governance

(Class II Officers)

Universe 405

Sample 185

(at 6% confidence interval)

Data Collected 90

Total Data

Collected

112

4.8 DESIGN OF QUESTIONNAIRE

A comprehensive structured questionnaire, (See Appendix-A) for the Class I and

Class II officers working on KM and on e- Governance were designed. Keeping in

view the time limitation of the respondents and to ensure speedy responses from the

82

respondents, the questionnaires were administered personally to all the respondents.

The questionnaires were so framed that the maximum information relating to the

objectives may be extracted from the respondents, on various aspects of the KM and

e- Governance. Most of the queries were to be responded on a five point (Likert)

scale. All the questions were close ended, so that the respondent time may be

optimally used. A few of the questions were framed in such a way that the

respondents may respond one or more options by tick mark. To cross check the

response of the respondents, some questions were common with different wording. A

few dummy questions were also asked from the respondent to keep him at ease. The

questionnaire was designed to develop the model for KM in e- governance. The data

collected through the questionnaires, was used for the development of the model. The

questionnaire was designed based on Gold, et al., Lee & Choi, Lee & Lee and Smith,

et al. models. Several e- governance professionals and KM professionals were

interviewed to modify the statements, the final questionnaire consists of nineteen

dimensions with eighty six statements (27 to measure KM infrastructure, 23 to

measure KM process, 23 to measure KM functions 18 to measure organizational

performance, 12 to measure critical success factors) as shown in Annexure 2. The

participants were asked to rate their perception towards the knowledge management

level within their departments on a five-point Likert-type scale with anchors from

“5- Strongly agree” to “1- Strongly disagree” and the relative importance for each

KM applications dimensions.

4.9 PILOT STUDY

The efficacy of the questionnaires (schedules) was tested on a small group of

executives working on KM in e- Governance (34) and the necessary modifications were

made on the basis of the feedback received from these respondents. The modified

questionnaires were used for collecting the final data. The questions were framed so as to

cover all the dimensions for the study.

4.9.1 CONTENT VALIDITY

The questionnaires have high content validity for the following reasons:

83

i) Identification of items were based on the logical analysis of evaluation of models

used in industries by different researches and the items of the scales were

thoroughly studied and got selected for the study.

ii) Framing of questions was done by involving professional judgment of

knowledgeable persons with vast experience of research and teaching of KM and

e- Governance.

4.9.2. RELIABILITY

Reliability of the different scales used in the questionnaire was tested while pre-

testing the questionnaire. Cronbach’s alpha test was applied for assessing the reliability

of scales. All the items which scored more than 0.6 were accepted as a scale in the

questionnaire but those items which scored less than 0.6 were dropped from the final

study. Scale used in for the success and hindrance factors has coefficient alpha of 0.914.

Below given are the details of each item.

Reliability Test for Knowledge Infrastructure Capability which includes:

a) Knowledge Technology Infrastructure (KTI 1-KTI 7)

Table 4.2: Cronbach’s Alpha Value for the Knowledge Technology Infrastructure

Cronbach's Alpha

Cronbach's Alpha Based

on Standardized Items N of Items

.956 .958 7

Knowledge

Technology

Infrastructure(

KTI1-KTI6)

Scale

Mean if

Item

Deleted

Scale

Variance if

Item

Deleted

Corrected

Item-Total

Correlation

Squared

Multiple

Correlation

Cronbach's

Alpha if Item

Deleted

Easy access to

information to do

the work

22.88 48.531 .920 .870 .944

84

IT supports joint

work regardless

of Time & space

22.91 47.234 .913 .908 .944

Brings

department closer

to public

22.85 48.978 .814 .816 .952

Links all

members of

department to one

another and to

general public

22.85 46.917 .929 .910 .943

Creates a central

repository

accessible to the

entire department

23.03 49.242 .746 .595 .958

Helps to search

new knowledge 22.97 47.242 .783 .766 .956

Recovers & uses

the knowledge

about products

&process

23.09 48.447 .861 .783 .948

Table 4.3: Cronbach’s Alpha Value for the Knowledge Structure

Cronbach's Alpha

Cronbach's Alpha Based on

Standardized Items N of Items

.919 .921 13

85

Knowledge Structure

Scale

Mean if

Item

Deleted

Scale

Variance

if Item

Deleted

Corrected

Item-Total

Correlation

Squared

Multiple

Correlation

Cronbach's

Alpha if

Item

Deleted

Decisions are made without

approvals 40.65 112.478 .672 .762 .912

Rules & Procedures are

written & followed 40.38 110.243 .853 .813 .906

Members can understand

not only own task but

others tasks

40.50 107.409 .848 .804 .905

Members are specialist in

their own part of work and

readily accessible

40.79 111.987 .719 .739 .911

Organization structure

promotes collective rather

than individualistic

behaviour

40.62 110.183 .787 .771 .918

There is an effective written

policy for application of

information/knowledge

Management

40.94 113.148 .277 .252 .012

Structure of department

supports interaction and

sharing of knowledge

40.59 113.159 .666 .710 .913

Structure uses partnership

or strategic alliance for

acquiring knowledge

40.56 114.072 .043 .438 .081

86

Knowledge/ Information

Management for e- gov is

responsibility of higher

officials

40.65 111.447 .644 .727 .914

Department bases our

performance on knowledge

creation

41.15 111.402 .697 .755 .911

Department members are

supportive of knowledge

sharing & creation

41.88 122.834 .276 .456 .927

Has standardized reward

system for sharing

knowledge

9.71 1.850 .073 .052 .020

Encourages employees to

go where they need for

knowledge regardless of

structure

41.12 110.774 .567 .561 .918

In the above mentioned table three items namely:

KS6- There is an effective written policy for application of information/knowledge

Management. KS 8-Structure uses partnership or strategic alliance for acquiring

knowledge. KS12- Has standardized reward system for sharing knowledge.

All the above mentioned items had Cronbach alpha less than 0.5 and so they were

excluded from the questionnaire.

87

Knowledge Culture (KCI1-KCI7)

Table 4.4: Cronbach’s Alpha Value for the Knowledge Culture

Cronbach's Alpha

Cronbach's Alpha Based

on Standardized Items N of Items

.865 .876 7

Knowledge Culture

Scale

Mean if

Item

Deleted

Scale

Variance if

Item

Deleted

Corrected

Item-Total

Correlation

Squared

Multiple

Correlation

Cronbach's

Alpha if Item

Deleted

Understands the

importance of

Knowledge for e-

governance

23.91 19.477 .381 .432 .890

Emp valued for their

expertise 23.56 18.799 .732 .695 .835

Emp are encouraged

to interact with other

members of the dept

23.62 16.789 .823 .735 .818

On job training &

learning are valued 23.53 19.348 .599 .592 .851

Encourages workers

to participate &

discuss in cross

department teams

23.56 18.133 .665 .540 .842

Vision & Objectives

of the organization

are clear to all

23.74 20.079 .671 .469 .846

Higher management

supports Knowledge

Management

23.62 17.758 .717 .596 .834

88

Knowledge Process Capabilities: Knowledge Acquisition ( KA1-KA6)

Table 4.5 : Cronbach’s Alpha Value for the Knowledge Acquisition

Cronbach's Alpha

Cronbach's Alpha Based on

Standardized Items N of Items

.858 .860 6

Scale

Mean if

Item

Deleted

Scale

Variance if

Item

Deleted

Corrected

Item-Total

Correlation

Squared

Multiple

Correlation

Cronbach's

Alpha if Item

Deleted

Has processes for

getting right

knowledge at right

time

17.26 21.898 .552 .365 .851

has process for creating

new knowledge frm

existing knowledge

17.88 18.895 .726 .772 .820

Has process for

acquiring knowledge

abt the suppliers

18.09 20.750 .704 .658 .827

Has process for

distributing knowledge

throughout the

department

17.15 21.644 .596 .382 .844

Has process for

exchanging knowledge 17.79 17.805 .837 .852 .796

Has process for

acquiring knowledge

abt new

processes/services

17.41 20.734 .511 .494 .863

89

Knowledge Process Capabilities: Knowledge Conversion (KC1-KC5)

Table 4.6: Cronbach’s Alpha Value for the Knowledge Conversion

Cronbach's Alpha

Cronbach's Alpha

Based on

Standardized Items N of Items

.086 .637 5

Scale

Mean if

Item

Deleted

Scale

Variance if

Item

Deleted

Corrected

Item-Total

Correlation

Squared

Multiple

Correlation

Cronbach's

Alpha if Item

Deleted

Have processes for

sorting knowledge 15.44 77.709 .033 .431 .082

Has process for

transferring

departmental

knowledge to

individuals

15.50 77.712 .031 .431 .083

Process for

absorbing

knowledge from

individuals exists

14.82 72.089 .434 .370 .024

Processe for

organizing

knowledge exists

13.50 11.833 .021 .189 .750

Processes for

replacing outdated

knowledge exists

15.79 73.987 .182 .250 .026

90

In the above mentioned table four items namely: KC1- Have processes for sorting

knowledge, KC 2-Has process for transferring departmental knowledge to individuals,

KC 3 - Process for absorbing knowledge from individuals exists, KC4- Processes for

replacing outdated knowledge exists. All the above mentioned items had Cronbach alpha

less than 0.5 and so they were excluded from the questionnaire.

Knowledge Process Capabilities: Knowledge Application( KAP1-KAP5)

Table 4.7: Cronbach’s Alpha Value for the Knowledge Application

Cronbach's Alpha

Cronbach's Alpha Based on

Standardized Items N of Items

.901 .906 5

Scale

Mean if

Item

Deleted

Scale

Variance

if Item

Deleted

Corrected

Item-Total

Correlation

Squared

Multiple

Correlatio

n

Cronbac

h's Alpha

if Item

Deleted

Process for applying

knowledge learned from

mistakes

14.47 15.045 .729 .619 .887

Processes for applying

knowledge learned from

experiences

14.00 18.061 .714 .571 .892

Processes for using

knowledge to solve new

problems

14.47 14.923 .744 .726 .883

Knowledge is used to

improve efficiency 14.18 15.725 .822 .747 .865

Knowledge is quickly

applied for critical

competitive needs

14.18 15.241 .812 .806 .866

91

Knowledge Process Capabilities: Knowledge Protection (KPC1-KPC7)

Table 4.8: Cronbach’s Alpha Value for the Knowledge Protection

Cronbach's Alpha Cronbach's Alpha Based on Standardized Items N of Items

.687 .688 5

Scale

Mean if

Item

Deleted

Scale

Variance if

Item

Deleted

Corrected

Item-Total

Correlation

Squared

Multiple

Correlation

Cronbach's

Alpha if Item

Deleted

Have processes to

protect knowledge

from inappropriate

use inside the

department

13.03 6.757 .579 .392 .679

Have processes to

protect knowledge

from inappropriate

use outside the

department

13.03 7.787 .363 .227 .668

Incentives for

protecting knowledge

from misuse

14.35 7.750 .297 .141 .698

Has technology that

restricts acess to some

source of knowledge

13.18 6.513 .506 .294 .607

Department stresses

representing

knowledge in

documents, databases

and software

13.24 6.852 .481 .278 .619

92

Knowledge Function Capability: Knowledge Capture ( KFCa1- KFCa4)

Table 4.9: Cronbach’s Alpha Value for the Knowledge Capture

Cronbach's Alpha Cronbach's Alpha Based on Standardized Items N of Items

.761 .767 4

Scale

Mean if

Item

Deleted

Scale

Variance if

Item

Deleted

Corrected

Item-Total

Correlation

Squared

Multiple

Correlation

Cronbach's

Alpha if Item

Deleted

Knowledge gets

captured prior to

retirement

11.24 5.640 .490 .388 .750

External Knowledge

is captured &

communicated to

everyone

10.65 5.326 .688 .499 .834

Captures knowledge

of lessons learnt and

best practices for

reuse

10.53 6.075 .588 .379 .895

encourages workers

to participate in cross

dept teams

10.65 6.053 .498 .381 .738

Knowledge Function Capability: Knowledge Creation: (KFC1-KFC5)

Table: 4.10 Cronbach’s Alpha Value for the Knowledge Creation.

Cronbach's Alpha Cronbach's Alpha Based on Standardized Items N of Items

.784 .783 6

93

Scale

Mean if

Item

Deleted

Scale

Variance if

Item

Deleted

Corrected

Item-Total

Correlation

Squared

Multiple

Correlation

Cronbach's

Alpha if Item

Deleted

Creates new

knowledge for

application across

different departments

18.44 11.406 .561 .442 .746

Creates operation

system for application

across functional

boundaries.

18.62 12.304 .422 .297 .776

Provides necessary

sources like internet,

publications to create

the knowledge i need

to fulfil my job

18.59 10.250 .607 .392 .732

Provides training to

create knowledge on

regular basis

18.32 10.529 .583 .432 .738

Our department

stresses on generating

new knowledge

18.56 10.860 .528 .423 .753

Department engages

in process of

distributing

knowledge among

different departments

18.35 11.690 .501 .448 .759

Knowledge Function Capability: Knowledge Sharing: (KFS1-KFS6)

Table: 4.11 Cronbach’s Alpha Value for the Knowledge Creation

94

Cronbach's Alpha Cronbach's Alpha Based on Standardized Items N of Items

.739 .757 6

Knowledge Sharing Scale

Mean if

Item

Deleted

Scale

Variance if

Item

Deleted

Corrected

Item-Total

Correlation

Squared

Multiple

Correlation

Cronbach's

Alpha if

Item

Deleted

Department engages

in process of

distributing

knowledge among

different departments

17.53 10.620 .547 .156 .884

Sharing of knowledge

& information exists

by directories &

experts

17.38 12.122 .450 .290 .717

Access of shared

documents with the

aid of taxonomy or

content management

exists

17.85 10.372 .514 .461 .891

Knowledge is shared

through story telling 17.88 10.289 .558 .282 .879

Knowledge is shared

by regularly

submitting knowledge

to central repository

18.21 9.381 .597 .130 .763

Reward system for

sharing knowledge

exists

17.91 10.689 .293 .119 .771

95

Knowledge Function Capability: Knowledge Utilization: (KFU1- KFU5)

Table 4.12: Cronbach’s Alpha Value for the Knowledge Utilization

Cronbach's Alpha

Cronbach's Alpha Based on

Standardized Items N of Items

.719 .742 5

Scale

Mean if

Item

Deleted

Scale

Variance if

Item

Deleted

Corrected

Item-Total

Correlation

Squared

Multiple

Correlation

Cronbach's

Alpha if Item

Deleted

engages in processes

which apply

experiential

knowledge across

functional boundaries

14.71 8.881 .374 .565 .709

Knowledge is

utilized for solving

new problems

14.74 8.564 .520 .460 .863

Knowledge is

utilized for decision

making

15.21 7.805 .528 .522 .752

Knowledge is

utilized for adjusting

strategic directions

15.38 7.031 .418 .546 .722

Able to apply &

locate knowledge to

changing competitive

condition

14.91 7.840 .641 .407 .816

96

Knowledge Function Capability: Training & Mentoring: (TMK1-TMK3)

Table: 4.13 Cronbach’s Alpha Value for Training & Mentoring.

Cronbach's Alpha

Cronbach's Alpha Based on

Standardized Items N of Items

.309 .331 3

Training &

mentoring for KM

Scale

Mean if

Item

Deleted

Scale

Variance if

Item

Deleted

Corrected

Item-Total

Correlation

Squared

Multiple

Correlation

Cronbach's

Alpha if Item

Deleted

Formal training is

provided for KM

practises

7.65 1.569 .173 .091 .230

Informal training is

provided for KM

practises

7.06 1.572 .302 .107 .011

Encourages

experienced worker

to transfer

knowledge to less

experienced worker

7.12 1.683 .072 .020 .456

In the above mentioned table all the three items namely TMK1: Formal training is

provided for KM practices, TMK2- Informal training is provided for KM

practices,TMK3- Encourages experienced worker to transfer knowledge to less

experienced worker. All the above mentioned items had Cronbach alpha less than 0.5 and

so they were excluded from the questionnaire.

97

Performance Productivity & Decision Making

Table 4.14 : Cronbach’s Alpha Value for Performance Productivity & Decision Making

(OP1- OP 18)

Cronbach's Alpha

Cronbach's Alpha Based on

Standardized Items N of Items

.843 .838 18

Performance

Productivity &

Decision Making

Scale

Mean if

Item

Deleted

Scale

Variance if

Item

Deleted

Corrected

Item-Total

Correlation

Squared

Multiple

Correlation

Cronbach's

Alpha if Item

Deleted

KM reduces rework 69.15 39.705 .260 .526 .843

KM increased

productivity 68.94 37.693 .459 .532 .834

KM enhances

collaborations in

departments

68.88 39.925 .322 .707 .840

KM improves

profitabily 69.06 36.542 .522 .672 .831

KM improves quality

of services 69.03 37.787 .460 .733 .834

KM improves faster

decision making 69.00 38.424 .437 .652 .836

KM in e- governance

improves better

decision making

68.76 38.004 .502 .760 .833

KM improves return

on investment 68.88 37.804 .453 .524 .835

98

KM improves

communications

among departments

69.03 36.817 .507 .653 .832

KM helps in faster

responses to the key

e- governance issues

68.91 37.840 .503 .605 .833

KM innovates e-

governance services 69.68 34.953 .566 .695 .829

KM improves

employee skills 68.97 37.545 .492 .754 .833

KM has improved &

created better way of

working

68.88 34.895 .769 .908 .818

KM has improved

learning/ adaptation

capabilities

69.06 36.421 .456 .680 .836

KM has increased

working performance

of employees

68.88 38.834 .359 .693 .839

KM has reduced

citizen response time

& better services

68.74 39.716 .336 .530 .840

KM helps in

streamlining internal

processes

68.91 41.780 .021 .607 .851

KM reduces

redundancy of

information &

knowledge

68.74 39.291 .403 .535 .837

99

Critical Success Factors: CSF1- CSF24

Table 4.15: Cronbach’s Alpha Value for Critical Success Factors

Cronbach's Alpha Cronbach's Alpha Based on Standardized Items N of Items

.969 .971 24

Performance

Productivity & Decision

Making

Scale Mean

if Item

Deleted

Scale

Variance if

Item Deleted

Corrected Item-

Total

Correlation

Cronbach's

Alpha if Item

Deleted

KM Strategy 69.15 39.705 .793 .968

Defined & communicated

KM objectives 68.94 37.693 .664 .969

Top Management

Commitment 68.88 39.925 .601 .969

Developing new roles &

responsibilities for KM 69.06 36.542 .691 .968

Designing of KMS for

easy usage 69.03 37.787 .732 .968

Focus on people factor 69.00 38.424 .743 .968

Development of team

oriented culture 68.76 38.004 .623 .969

Creation of trust among

knowledge workers 68.88 37.804 .831 .967

Comprehensive user

training 69.03 36.817 .703 .968

Introduction of monetary

& non monetary incentives

& rewards

68.91 37.840 .637 .969

100

change in organizational

structures & processes 69.68 34.953 .874 .967

Performance measurement 68.97 37.545 .872 .967

Management, Leadership

& support 68.88 34.895 .819 .967

Organizational Culture 69.06 36.421 .800 .967

Structure, Roles &

Responsibilities 68.88 38.834 .775 .968

Information Technology 68.74 39.716 .762 .968

Organizational

Infrastructure 68.91 41.780 .713 .968

Process & Activities 68.74 39.291 .872 .967

Rewarding & motivation 69.15 39.705 .830 .967

Training & Education 68.94 37.693 .853 .967

Transfer 68.88 39.925 .790 .968

Resource Constrains 69.06 36.542 .811 .967

HRM 69.03 37.787 .738 .968

Impact of KM on e- gov in

PMC 69.00 38.424 .469 .971

4.10 DATA COLLECTION

Data was collected by two methods:

Qualitative Technique: Here the researcher did rigorous observation,

interviewing with the associated personas which helped in identifying the

independent and dependent variables for the further study which was initially

derived from literature review and analyzed with the present scenario, went

through validity and reliability test and then these variables were finalized to get

included for the final quantitative study.

Quantitative Technique: This included the filling of the questionnaire from the

respondents. Data was collected between October, 2011 to May, 2013.