paper on lg

8/2/2019 paper on lg

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Introduction

Nigeria is a federation made up of the federal, state and local governments. Presently, there arethirty six (36) states (and the federal capital territory, Abuja) and seven hundred and seventy four

(774) local governments and area councils. The 3 tiers government system is necessitated by the

fact that Nigeria being a vast country with overwhelming human population and diverse culture

needs a good measure of decentralization for sound administration and effective development.The Nigerian local government administration can rightly be traced back to the traditional local

administration system that existed prior to the colonial era. This was followed by the Native

Authority System which was introduced to better service the colonial authority. At the time ofindependence in 1960, local government was essentially a regional responsibility. During the

early military era of 1967 to 1976, local government system remained more or less a

decentralized extension of the states, with local governments performing essentially, residualroles for their military overlords at the state level (Akhabue, 2007) and (Olanipekun, 1988).

In the later military era (1976 1979), effort was made to transform the basic roles of local

government as demonstrated in the 1976 local government reform. This reform established local

governments as the 3rd tier of government, with its own identity, power and sources of revenue.

The need for devolution of power instead of delegation of functions to local governments wasunderscored in the reform. The objective was to entrust political responsibility to where it was

most crucial and beneficial. The principle of participatory democracy was put in place andpolitical responsibility of every Nigerian was enshrined in the constitution. Constitutional roles

of the local government administrations in Nigeria include provision of basic infrastructure,

establishment and maintenance of primary schools, agriculture and veterinary services, townplanning and so on (Olanipekun, 1988), (Ekpo, 1998).

In addition, local government should provide inspection of meat and abattoirs, information and

public enlightenment, scholarships and bursaries, public libraries and reading rooms, fireservices, support for arts and culture and control of pollution. Local governments should also

provide control of beggars and prostitution, homes for destitutes, the infirm and orphans public

housing programmes and regulation and control of buildings. Finally they back roll the

operations of commercial undertakings, traffic and parking and pipe sewerage systems

LOCAL GOVERNMENT ADMINISTRATIVE STRUCTURE

Successive governments have aspired to put in place stable local government structures that arecapable of mobilizing local people and their resources for sustainable local as well as national

development. Every local government is formulated according to the structure shown in Figure

1. Each local government has a Policy Making Body, the Administrative Body and TraditionalRulers (Olanipekun, 1988). The policy making body comprises of an elected or appointed

Executive Chairman, Vice Chairman, Supervisory Councillors and Councillors. The supervisory

councellors oversee projects, units and programmes. The Counsellors preside over local

government legislative matters. They also ensure that the executive arm operates with theconfine of the law. The Administrative Body comprises of The Head of Personnel Management

(as the Chief executive), Heads of Departments, and Subordinate Staff. Various departments at

the local government include but not limited to the following:a. General and Administration DepartmentHeaded by the Deputy Secretaryb. Treasury DepartmentHeaded by the Treasurerc. Works DepartmentHeaded by the Civil Engineer/ Technical Officer


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d. Health DepartmentHeaded by the Principal Health Superintendente. The Maternity Division of the Medical DepartmentHeaded by the Senior Midwifery Sisterf. The Dispensary Division of the Medical Department Headed by the Higher Pharmacy

Officer:

g. A Farm Division - Headed by the Farm Manager.

Each arm of the policy making body as well as the executive department, has specific functions

to perform. These constitute the functions of Local Government in Nigeria. In order to preserve

the traditional position of our Obas and Chiefs, The government put in place a TraditionalCouncil for each Local Government authority area or a group of Local Government authority

areas over which a traditional ruler has suzerainty.

A Traditional Council consists of traditional office holders, the Chairman of the LocalGovernment authority, one or two traditional representatives of each Local Government

authority council, as may be considered appropriate and any other person(s) who may be desired,

in order to make the traditional Council broadly representative of the major facts of life in theentire area. The major functions of the traditional rulers are to:

a. advise the Local Government authority or a group of Local Government authorities onmatters referred to them by the elected council,

b. discus common problems and make suggestions to the Local Government authority orauthorities in the area,

c. make representations or express opinions to Local Government authorities, on mattersthat may not strictly be the responsibility of the Local Government authorities, providedthey are of concern to the area as a whole,

d. determine or advise the traditional ruler on all matters including the conferment oftraditional titles and appointments

Policy Making Body

Administrative Body

Councellors

Traditional

Rulers

Figure 1: Nigeria local government structure

Executive Chairman

Executive Vice Chairman

Executive Secretary

Supervisory Councellors

Head of Personnel

Head De artment 1

Head De artment Head, Department n

Head, Unit 1 Head, Unit n Head, Unit 1 Head, Unit 1 Head, Unit n


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e. advise on and determine customary laws and practices on all matters referred to itincluding those related to land.

Local governments in Nigeria are bedevilled with a number of problems including (Akhabue,

2007; Olanipekun, 1988):

a. Inadequate constitutional provisions: even though the 1999 constitution guarantees theexistence of democratically elected local government councils, there is no express

provision in the constitution regulating the tenure of local government councils as it

provided for the president and state governors. As a result of the singular omission oroversight, the various state legislatures now determines the tenure of its elected councils

and therein lies the prescription for the unfolding chaos in Nigeria local government

system. The result is a situation where there is no uniformity of tenure across the countryof elected local government officials. While a few states graciously accord local

governments a 3year tenure, majority operate a maximum of 2year tenure.

b. Undue interference by state governments: it is now a common practice that the tenure of

local government administration is unceremonious terminated by the state governors and

legislatures before the expiration of the mandate given by the people during elections.After the terminations, elected council chiefs are replaced with unelected and selected

individuals and political associates under the nomenclature of caretaker committee.The tenure of the caretaker committee may be indefinite depending on the extent that a

governor is satisfied or convenient for the state government to conduct local council

elections.c. Lack of continuity by succeeding Governments: there is a pattern where succeeding

government or caretaker committee abandon the programmes and projects of the

immediate government to embrace new ones. This leads to economic and mental wastage

as well as the retrogression of development.d. Unemployment: this is a major problem confronting local government as well as the

entire country generally. unemployment has led to general under-feeding among the

majority of the population since the working teams are smaller than the consuming teams.

Another consequent of employment is insecurity arising from the engagement of theunemployed youths in criminal acts.

e. Shortage of Skilled Man Power: most local government do not have the sufficient

professional manpower needs for successful administration. There are no competent andqualified hands to handle or execute people oriented programmes or projects.

f. Financial Constraints: Revenues of most local governments are by far lower than what is

required. This has propelled inability to execute rich programmes and projects, inabilityto implement good staff welfare, inability to implement modern day administratrative

system anchored on ICT and inability to foster or promote staff productivity through

training and seminars.

ICT AS A TOOL FOR LOCAL GOVERNMENT ADMINISTRATIONThe administration of most local governments in Nigeria is by the traditional method. It involves

direct involvement of human agents in communication and management. The traditional methodis devoid of the use of ICT for control, budgeting, forecasting, planning, staffing and other

administrative or managerial tasks. Though the method is cheaper, it is slow and expensive.

Other problems include duplication of efforts, redundancy, lack of standard, bypassing of


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protocol, communication failure, loss of documents on transits, victimization, high handedness,

abuse of privileges, fatigue and so on. These problems continue to hinder the administrativesystem from delivering good governance to the doorstep of the citizenry. People have continued

to express their dissatisfactions with poor governance through poor voter turnout during

elections, lower levels of public participation in government related programmes, disobedient to

public order, protest of policies considered as obnoxious, tax invasions among others(Guchteneire and Mlikota, 2010).

With the rapid spread of Information and Communication Technologies (ICTs), newopportunities evolved for the revival of public discourse and improved governance effectiveness

and efficiency. ICTs offer concrete opportunities for local and national governments towards the

improvement of their performance in terms of transparency, participation and decentralization.

The mainstreaming of ICTs within planning and design of development strategies helps to

strengthen the establishment of efficient, effective and transparent governance systems. On-line

tools can significantly improve the rendering of services and information flows from

administrations to their constituencies. It also enhances communication among administrations

and citizens as well as offering unique opportunities for broadened citizen involvement andparticipation in the decision-making process in standard and genuine manners (Ogbomo, 2009;

Boyoung, 2001; Osnaghi, 2010; Guchteneire and Mlikota, 2010). ICT is particularly relevant inthe developing countries context, where series of transformation to democratic regimes is

currently taking place. It is also relevant in combating pronounced problems such as corruption

of public administration and lack of transparency. In the administration of the local governments,ICT can be used as a tool in the following ways (Guchteneire and Mlikota, 2010; Jensen, 2002;

Ofei_Aboagye, 2009; Acharya, 2009; Bekele et al, 2005; Olabode and Akingbesote, 2007;

Mitulla and Waema, 2005):

a. In transparency and due process: Conducting transactions in line with laid down rulesusing systems supported by ICT has proved to be very effective in fighting corruption. It

reduces significantly, transaction costs leading to savings. An example of the efficient use

of ICTs to fight corruption is the launching of the Electronic Graft Management (EGM)

project in Kenya (Guchteneire and Mlikota, 2010). The EGM project offered a corruptionreporting facility in six towns with existing Internet infrastructure. Anonymity of users

was ensured and reports were transmitted to EGM centers for analysis and follow-up with

relevant authorities.b. Provision of cheaper, more efficient and faster services: This leads to enhanced service

delivery. Cheaper and faster service delivery systems enable citizens to obtain

information and to carry out transactions 24 hours a day, seven days a week, and areparticularly suitable for simple administrative transactions, such as requests for permits,

or submissions of tax files.

c. Fostering public-private-partnership policy-making: Through the facilitation of

collaboration and the sharing of information within government agencies and betweengovernment and the people, new opportunities continue to emerge for promoting

development. A significant example on the use of ICTs for collaboration and sharing is

the Today I decide (TOM) portal launched by the Estonian government in 2001. TOMprovided an opportunity for citizens to become involved in policy-making and to

comment on draft laws that are published on the portal. The public can also submit their


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own proposals for laws or policies, which are taken into consideration by the government

(Heeks, 1998).d. Improvement of the internal workings of government to be externally-oriented and more

people-oriented.

e. Attracting foreign investments through the provision of faster access to information and

government services.

LITERATURE REVIEW

In (Olabode and Akingbesote, 2007), a documentation on the preconditions for ICTimplementation and virtual bureaucracy in the local governments is presented. A technical

framework (Technical Model) for implementation is also presented with its basic components of

ICT infrastructures and Information systems. The basic infrastructure include personalcomputers local area network(s), user identification and authorization systems and basic

software. Document management system (DMS), E-mail systems and Web pages of local

government and e-democracy tools were the basic information system needs. (Pudjianto and

Hangjung, 2011) presents a conceptual framework for analyzing the assimilation of governance

in the context of ICT innovation in the developing countries based on Technological-Organizational-Environmental (TOE) Framework, Innovation and Diffusion Theory.

Assimilation was analyzed as single stage technology diffusion process. An Innovation diffusiontheory was coined with TOE framework to explain how assimilation process is affected by ICT

expertise, ICT infrastructure, Top management support, organizational compatibility, extend

coordination, regulatory environment, and competition. The implementation of this frameworkreveals that ICT expertise, Top Management Support, Organization Compatibility, Regulatory

and Competition, had a positive influence on assimilation of ICT into governance.

It is also reveal that environmental factor plays a key role in the incursion of ICT intogovernance as lack of a supportive regulatory environment for ICT have a significant negative

effect on assimilation. Similarly in the organizational factors, it was stated that organizational

compatibility significantly impacts ICT. This occur because organizational compatibility

influence the degree of acceptance of ICT in adoption and assimilation systems. This implies thatorganization that already has organizational changes toward ICT implementation will definitely

experience increased influence of compatibility towards e-governance. In term of Technological

factors, it was stated that infrastructure was not of much essential in the penetration of ICTwhich contradicts past researches most of which exhibited a significant association of ICT

infrastructure with ICT adoption. The reasons adduced for this discrepancy include increasing

rate of alternative channel to accessing the internet and the booming mobile communicationwhich further increases the penetration of internet to the last mile users. These reasons may

ultimately lead to lesser dependent of ICT infrastructures factor.

In (Bwalya, 2009), factors affecting the adoption of ICT into governance in Zambia is presented.Emphasis was on the impact of ICT on the nations Health and Immigration Management

Systems. The challenges, opportunities, and issues together with e-government adoption criteria

regarding successful encapsulation of e-government into the Zambian contextual environmentwere also assessed. It was reported that lack of adequate ICT infrastructure and political will,

provision of content in English other than local languages, lack of proper change management

procedures, non-contextualization of e-government practices and so on are problems


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contributing to the delay in the incursion of ICT to governance in Zambia. A conceptual model

which offers balanced e-government adoption criteria involving a combination of electronic andparticipatory services was proposed. The model serves as a start-point for any model which can

later be replicated to include the whole lot of Southern African Development Community

(SADC) countries given the similarity in the contextual environment. Based on findings from the

implementation of the model, the author concluded that government should create an enablingenvironment for the adoption of ICT in governance, play a leading role in developing the ICT

infrastructure and take full advantage of various initiatives taken by the international community

to ensure that ICT becomes a veritable tool for productive governance.

Factors affecting successful implementation of ICT project in government is presented in

(Gichoya, 2005). Results of literature review of case studies from both developed and developingcountries and preliminary studies grounded in the Kenya e-Government reality were presented.

The key factors synthesised and categorised under common broad categories resulting in a rich

picture of ICT implementation experience that helps to identify possible solutions were also

presented. A descriptive framework for categorising these factors is proposed. The input

variables are categorised into factors for success (drivers and enablers), and factors for failure(barriers and inhibitors). The output variables are categorized into organisational and

technological benefits. Finally, an action for success was proposed. This action includessuggestions for increasing the impact of factors for success while reducing the impact of factors

for failure and use of available good practice. In his conclusion, the author reported that for the

development needs of ICT projects, those involved in their design, implementation andmanagement in the developing countries must improve their capacity to address the specific

contextual characteristics of the organisation, sector, country or region within which their work

is located. Though the paper does not classify the factors in terms of their influence, however,

vision and strategy and government support were considered important for success while lack offunds and poor infrastructure were considered as major factors for failure.

In view of the findings from the literature review, the main objective of this paper is to formulate

some indices or variables and use them for the statistical analysis of the level or incursion of ICT

into local government administration in Nigeria. The other objective is to determine somerelevant factors responsible for the current level of ICT at the local government level using

relationship existing among some formulated and associated indices.

RESEARCH MODEL

The indices or variables that can be used to construct a research instrument for collecting

relevant data for the statistical analysis of the level of incursion of ICT into local government

administration in Nigeria are numerous and are related to one another. Based on this, a model for

computing the impact of some factors derived from a set of variables and based on data collectedfrom a group of respondents is formulated as follows:


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where Rs represents the sth

respondent, bs,t represents the assessment of the tth

index by sth

respondent, Zt represents the tth

index and i is the number of indices.

Factor analysis by principal components (FAPC) approach was adopted for the implementation

of the model. FAPC is used to generate clusters of indices that form factors with their respective

percentage contribution to the present level of ICT at the local government level. The generationof the clusters by statistical analysis is in the stages shown in Figure 2 (Iwasokun et al, 2011).

The mean and variance of the scores of each decision variable given by the respondents formedpart of the descriptive statistics. The degree of pair-wise relationships among the indices is

defined by the correlation matrix. A value of correlation greater than zero implies a positive

relationship while a value less than zero shows a negative relationship. The correlation value is

zero when there is no relationship between indices. The results from the Bartletts test of

sphericity present the adequacy level of the sample from the population. Kaiser-Mayer Olkin

(KMO) test is used to confirm sample adequacy. A set of factors which are generally referred to

as familiar factors exists in factor analysis. Each of these factors loads on some related

variables. Another set of factors, which are unconnected to each of the variables also exist. The

proportion of the variance of a variable explained by the familiar factor is called the

communality of the variable (Loehlin 1999 & Bryant and Yarnold 1995). The factor loadingderived for a specific variable form the agreement level (correlations) between the factor and the

variables normal scores. Each factor defines a generalization domain which is qualitatively

separate from those presented by other factors. Factor loading is the measure of generalization

between each variable and each of the factors. The contribution of a variable to a factor increases

as the loading increases from zero in the positive direction. Varimax, equamax, quartimax and

promax are used in SPSS for orthogonal rotation which is used for establishing a high correlation

Descriptive

Statistics

Correlation

Matrix

Bartlet &

KMO

Tests

Communalities

Initial factor

Loading

Rotated

factor

Loading

Factor score

coefficient

matrix

Eigenvalue

StatisticalAnal sis


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between variables and factors. The component score matrix of the factors on its own is generated

for evaluating the contributions of each of the variables to the present state of ICT in the Nigeria

local governments. The eigenvalue and percentage variance of the extracted factors are generated

for evaluating the contribution of each factor (Iwasokun et al, 2011).

DATA SURVEY AND COLLECTIONThe indices which were formulated towards achieving the objectives of this research are shown

in appendix I. Appendix I presents a research instrument used for data collection by survey

method. The first part of the research instrument provides vital information about each

respondent while the second part provides five columns for respondents to rank each of the thirty

six indices on the grade ofExcellent, Very Good, Good, Average or Poor. The research

instrument was surveyed on some selected local governments across the thirty six states and the

Federal Capital Territory (FCT), Abuja. In each case, two officers from the policy making body

and twenty officers from the different levels in the administrative body were surveyed. The

summary of the number of research instruments that were duly completed and returned is

presented in Table 1.

Table 1: Summary of the survey across the geo-political zones

Zone State No. of localgovernments

No. of localgovernments.

surveyed

Total Instrumentretuned by policy

makers

Totalinstrumentreturned by

administrators

Totalinstrumentreturned

TotalInstrument

not returned

NorthEast

Adamawa 21 0 0 0 0 0

Bauchi 19 10 17 179 196 24

Borno 27 0 0 0 0 0

Gombe 11 7 14 136 150 4

Taraba 16 7 12 132 144 10

Yobe 17 10 20 194 214 6NorthWest

Kaduna 23 14 23 267 290 18

Katsina 35 0 0 0 0 0

Kano 45 23 44 251 295 211

Kebbi 21 18 35 356 391 5

Sokoto 23 0 0 0 0 0

Jigawa 26 0 0 0 0 0

Zamfara 15 5 10 92 102 8

NorthCentral

Benue 23 22 41 406 447 37

Kogi 21 21 41 420 461 1

Kwara 15 15 28 279 307 23

Nasarawa 13 10 19 200 219 1

Niger 25 18 36 360 396 0

Plateau 17 12 23 234 257 7

FCT 6 6 12 120 132 0

SouthEast

Anambra 21 15 21 287 308 22

Enugu 16 11 21 219 240 2

Imo 27 18 35 349 384 12

Abia 18 11 20 204 224 18Ebonyi 12 6 9 118 127 5

SouthSouth

Akwa Ibom 31 18 32 358 390 6

Bayelsa 8 5 10 89 99 11

Cross River 20 11 21 220 241 1

Edo 15 15 30 300 330 0

Delta 25 21 41 413 454 8

Rivers 23 13 23 245 268 18

SouthWest

Ekiti 16 16 32 320 352 0

Lagos 20 20 39 338 377 63

Ogun 20 19 37 367 404 14

Ondo 18 18 36 360 396 0

Osun 30 23 45 453 498 8Oyo 35 25 46 457 503 47

Total 774 463 873 8723 9596 590


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A total of ten thousand one hundred and eighty six (10186) copies of the research instrument

were administered. During the process of administration, the researchers were physically present

in 23, 29, 30, 37, 35 and 70 local governments in the North-East, North-West, North-Central,

South-East, South-South and South-West geopolitical zone respectively. With a view to cut the

cost associated with transportation over long distances, copies of the research instrument where

administered through contact agents in the remaining 239 local governments. The agents

received scanned copies of the research instruments through email. Duly completed and returned

research instruments were sent back to the researchers through postal service. In all, nine thousand,

five hundred and ninety six (9596) respondents (including executive and administrative officers) returned

duly completed research instruments from the four hundred and sixty three (463) surveyed local

governments. In the local governments personally visited by the researchers, follow-up meetings and

personal interviews were conducted with a view to verify and validate the responses.

RESULTS AND INTERPRETATION

Factor analysis by principal components using SPSS was performed on the data obtained from 9596 duly

completed and returned research instruments. The data were obtained by assigning values of 5, 4, 3, 2

and 1 to the linguistic form Excellent, Very Good, Good, Average and Poor respectively. Table 2

presents the descriptive data showing the means and variance of the overall rating of the level of

incursion of ICT into the local governments based on each of the indices. Appendix 1 provides index to

the variable names (indices) shown in Table 2.

Table 2: Descriptive Statistics

Variable Mean Variance

STASTA 3.55 .713

STAMAN 3.14 1.531

STACOM 3.31 .957

MANCOM 3.02 1.117

INTLOC 3.14 1.090

LOCSTA 3.15 .88

LOCFED 2. 7 1.203

RECKEP 2.46 .495DATGEN 2.84 .487

DISCIP 2.72 .814

FUNDAL 2.48 .72

CLAGRA 2. 9 .58

FINRET 2.18 . 85

EMPGEN 2.97 . 38

REVGEN 2.82 .971

LOAADV 2.28 .732

PROMON 2.91 . 15

TENBID 2.88 1.297

ACQPRO 3.1 .887

STATRA 3.31 .42

SEMCON 3.52 . 03

SALPAY 2.71 .559

ELEMAT 3.00 .565

GENADM 2.43 .898

TREMAN 2.41 .377HEAMAN 2. 5 .7 9

FARWRK 2.07 .945

INFMON 2.52 . 32

JUSDIS 1.99 .720

DEBATE 2.39 .55

TRAFIC 2.83 .589

DISPRE 2.40 1.381

DISMAN 2. 3 . 93

SOCPRO 2.93 .48

PUBENL 2.84 1.420

ENTREC 2.73 .811


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The mean and variance of the overall rating of staff-staff communication (STASTA) are 3.55 (71.00%)

and 0.713 respectively while the mean and standard deviation of the rating on staff-management

communication (STAMAN) are 3.14 (62.80%) and 1.531 respectively. These mean values show that on

the average, the respondents agreed that ICT provides between good and very good (midway between

the two) support for staff-staff communication and just good (a little above good) support for staff-

management communication. The Variance of 0.713 and 1.531 represent the standard difference

between the mean and the response values for staff-staff communication and staff-management

communication respectively.

The communalities of the performance indices are presented in Table 3. The Table shows that the

communalities of staff-staff communication (STASTA) and staff-management communication

(STAMAN) are 0.805 and 0.890 respectively. These imply that 80.50% of the variance in s taff-staff

communication can be explained by the extracted factors while the remaining 19.50% is attributed to

extraneous factors. Similarly, 89.00% of the variance in staff-management communication can be

explained by the extracted factors, while the remaining 11.00% is attributed to extraneous factors.

Table 3: Communalities of variables

Variable Initial Extraction

STASTA 1.000 .805

STAMAN 1.000 .890

STACOM 1.000 .853

MANCOM 1.000 .900

INTLOC 1.000 .860

LOCSTA 1.000 .904

LOCFED 1.000 .891

RECKEP 1.000 .921

DATGEN 1.000 .761

DISCIP 1.000 .874

FUNDAL 1.000 .871

CLAGRA 1.000 .650

FINRET 1.000 .908

EMPGEN 1.000 .877

REVGEN 1.000 .751

LOAADV 1.000 .806

PROMON 1.000 .829

TENBID 1.000 .861

ACQPRO 1.000 .881

STATRA 1.000 .767

SEMCON 1.000 .874

SALPAY 1.000 .829

ELEMAT 1.000 .803

GENADM 1.000 .921

TREMAN 1.000 .820

HEAMAN 1.000 .808

FARWRK 1.000 .895

INFMON 1.000 .860

JUSDIS 1.000 .879

DEBATE 1.000 .849

TRAFIC 1.000 .818

DISPRE 1.000 .824

DISMAN 1.000 .793

SOCPRO 1.000 .843

PUBENL 1.000 .869

ENTREC 1.000 .883


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The 36 x 36 correlation matrix obtained from analysis could not be displayed because of the need to

minimize the size of this paper. The matrix shows that highest correlation of 0.839 exists between impact

on staff-community communication (STACOM) and impact on staff-management communication

(STAMAN). The next highest correlation of 0.825 exists between impact on management-community

communication (MANCOM) and impact on staff-management communication (STAMAN). The

implication of the former is that Impact on staff-community communication is very likely to share same

factor with Impact on staff-management communication. Similarly, in the latter, Impact on management-

community communication (MANCOM) is very likely to share same factor with Impact on staff-

management communication (STAMAN). The least correlation of -0.668 exists between impact on staff-

management communication (STAMAN)and Impact on enforcement of discipline (DISCIP). This means

that impact staff management communication and Impact on enforcement of discipline are not likely to

share same factor.

The Bartlett's test of sphericity is used for the confirmation of the adequacy of the sample population.

Bartlett's test probed adequacy by testing the null hypothesis that the variables in the population

correlation matrix are uncorrelated and inadequate. The hypothesis is rejected only on the ground that the

observed significance level is 0.0000. For this analysis, the Bartletts test of sphericity produces a 2

of

387772.173 with a significance level of 0.0000, which confirms the adequacy of the sample population.

The Kaiser-Meyer-Olkin (KMO) test is another adequacy test. A satisfactory factor analysis is allowed to

proceed only if the sampling adequacy value is greater than 0.5. The Kaiser-Mayer Olkin (KMO) test

produces a measure of 0.632 for this analysis. The validity of subsequent results is therefore confirmed.

These adequacy and validity results are good indicators of the suitability of the application of factor

analysis.

Table 4: Extracted factor loadings

Component

1 2 3 4 5 6

STAMAN .918

STACOM .864

MANCOM .847

INTLOC .795

GENADM .767

DISPRE -.757

STASTA .744

LOCFED .733 -.454

EMPGEN .731

DISCIP -.727

TENBID .702

REVGEN .692

PUBENL .692 -.447

ACQPRO .656

LOCSTA .583 -.473

HEAMAN .581 .454

FINRET .566 .450

FUNDAL -.438

FARWRK .855

INFMON .795

LOAADV .731

CLAGRA .665

TREMAN .411 .545

PROMON .516

STATRA -.470

SALPAY .568 -.448

SEMCON .526 .470

DISMAN .498 .461

JUSDIS .666

DEBATE .534 .641

ELEMAT -.571

DATGEN .522

RECKEP .519 -.490

SOCPRO .456 .461 -.519

ENTREC .439

TRAFIC


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The initial factor extractions are often achieved in factor analysis by principal components using two

different approaches. In the first approach, specific number of factors is specified for extraction while in

the second approach, the numbers of factors to be extracted are specified on the basis of a Social

Science rule which states that only the variables with loadings equal to or greater than 0.4 should be

considered meaningful and extracted for factor analysis (Iwasokun et al, 2011). The latter rule is appliedon the initial component matrix generated and the extracted factor loadings obtained for this research is

presented in Table 4 which reveals the extraction of six factors with their variables loading.

Motivated by the need to obtain a more meaningful form of variables and factor mapping along principal

axis, the obtained components was orthogonally rotated using varimax, promax, equamax and quartimax

transformations. The results for promax presented in Table 5 was used for further analysis because it

turned out to be the best among others..

Table 5: factor Rotation by Promax

Variable Component

1 2 3 4 5 6

LOCFED .917

TENBID .909

STAMAN .831

PUBENL .827

DISCIP -.812

DISPRE -.795

MANCOM .767

STACOM .762

STASTA .751

INTLOC .652

REVGEN .647

EMPGEN .590

GENADM .525 .501

ACQPRO .524

SOCPRO .789

TREMAN .667

PROMON .662

INFMON -.409 .632 .584

FINRET .545

FARWRK .859

DEBATE .794 .548

JUSDIS .500 -.411 .785

LOAADV .728

HEAMAN .443 .523

SALPAY .891

DISMAN .846

FUNDAL .727

CLAGRA .431 .450

RECKEP .772

DATGEN .715

ELEMAT .526 -.575

LOCSTA .495 .534SEMCON .781

STATRA .629

ENTREC .602

TRAFIC .445

Table 5 reveals six factors with their corresponding loadings as follows:


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Factor 1- Communication and Development, loads on

a. Impact on local-federal government communication (LOCFED)b. Impact on tender and bidding (TENBID)c. Impact on staff-management communication (STAMAN)d. Impact on public enlightenment (PUBENL)e. Impact on enforcement of discipline (DISCIP)f. Impact on disaster prevention (DISPRE)g. Impact on management-community communication (MANCOM)h. Impact on staff-community communication (STACOM)i. Impact on staff-staff communication (STASTA)

j. Impact on inter local government communication (INTLOC)k. Impact on revenue generation (REVGEN)l. Impact on employment generation (EMPGEN)m. Impact on general administration (GENADM)n. Impact on acquisitions and procurements (ACQPRO)

Factor 2 Financial and social commitment, loads on

a. Impact on social programmes (SOCPRO)b. Impact on treasury management (TREMAN)c. Impact on project monitoring (PROMON)d. Impact on infrastructure monitoring (INFMON)e. Impact on financial retirements (FINRET)

Factor 3 Services, loads on

a. Impact on farm work (FARWRK)

b. Impact on house debate and deliberations (DEBATE))

c. impact on justice dispensation (JUSDIS)

D. Impact on loans and advances (LOAADV)

e. Impact on health management (HEAMAN)

Factor 4 Welfare and Harmony, loads on

a. Impact on salary and payroll (SALPAY)

b. Impact on dispute management (DISMAN)

c. Impact on fund allocation (FUNDAL)

d. Impact on claims and grants (CLAGRA)

Factor 5 Record and Data management, loads on

a. Impact on record keeping (RECKEP)

b. Impact on data generation (DATGEN)

c. Impact on electoral matters (ELEMAT)

d. Impact on local government-state communication (LOCSTA)

Factor 6 Staff development, loads on

a. Impact on seminars and conferences (SEMCON)

b. Impact on staff training (STATRA)

c. Impact on entertainment and recreation (ENTREC)

d. Impact on traffic control (TRAFIC)


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The results placed high emphasis on using ICT as a veritable tool for communication and development in

the local governments. Good and free-flow communication aided by ICT is important for effective, stable

and smooth administration, services and management. This equally promotes participation and

decentralization. These findings corroborated the position held in (Ogbomo, 2009; Boyong, 2001;

Osnaghi, 2010, Guchteneire and Milikota, 2010) that ICT enhances communication among administrators

and citizens and as well as offering unique opportunities for broadened citizens involvement and

participation in governance. The results equally show the importance of ICT towards financial and social

commitments, services, welfare and harmony, record and data management as well as staff

development. This also is in line with the views presented in (Jensen, 2002; Ofei-Aboanye, 2009;

Acharya, 2009 and Bekele et al., 2005) that ICT is fast emerging as tool for cheaper and more efficient

social service, community satisfaction, participatory governance and welfare development.

A factor was estimated as a linear combination of the original variables. Table 6 presents the coefficient

matrix representing the factor score generated for the research.

The coefficient matrix is majorly used for estimating the level of incursion of ICT into local government

administration according to the view of each respondent to each of the extracted factors. This is achieved

Table 6: Factor scores coefficient matrix

Component

Variable 1 2 3 4 5 6

STASTA .081 .058 -.021 .130 .024 .010

STAMAN .091 .034 .019 -.006 -.009 -.023

STACOM .082 .048 .010 .017 -.010 .064

MANCOM .085 .017 .023 -.037 .011 -.056

INTLOC .069 .050 -.045 -.064 .006 -.035

LOCSTA .032 .118 -.081 .002 .196 -.096

LOCFED .108 -.063 -.043 .035 .083 -.031

RECKEP .005 .048 .015 -.002 .269 -.037

DATGEN -.010 -.033 -.022 .021 .261 .056

DISCIP -.094 .035 .001 .014 .011 .132

FUNDAL -.013 -.025 .067 .266 .000 .012

CLAGRA -.018 .096 .067 .158 -.068 -.067

FINRET .015 .131 .021 -.061 -.107 -.035

EMPGEN .061 .064 .023 .024 -.026 .109

REVGEN .072 .004 .033 -.049 -.082 -.103

LOAADV -.005 .008 .179 -.063 -.060 -.059

PROMON -.007 .146 .058 .007 .055 .034

TENBID .110 -.110 .069 .023 -.004 .084

ACQPRO .056 .026 -.014 -.036 .120 .165

STATRA .034 -.055 .006 .018 .073 .272

SEMCON -.029 .015 -.040 -.005 -.019 .324

SALPAY .012 .003 -.046 .316 .047 -.019

ELEMAT .002 .134 -.044 .090 -.204 .026

GENADM .050 .121 -.056 -.022 .023 -.086

TREMAN .001 .156 .025 .038 -.066 -.019

HEAMAN .048 .007 .155 -.046 -.150 .111

FARWRK -.023 .015 .214 -.027 -.037 -.016

INFMON -.056 .138 .129 -.010 .021 .064

JUSDIS .069 -.141 .219 .095 .024 .002

DEBATE -.003 -.004 .187 .033 .167 .043

TRAFIC -.019 -.031 .106 .079 .000 .208

DISPRE -.090 .013 .024 .012 .045 .010

DISMAN .002 .005 -.013 .301 -.038 .007

SOCPRO -.015 .198 -.096 -.060 .114 .006

PUBENL .097 -.065 -.017 .000 -.021 .106

ENTREC .008 .063 .008 -.062 -.088 .251


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by using a linear equation of the weighted standard scores of each respondent on the variables as follows

(Iwasokun et al, 2011):

where Mb,c represents the contribution of bth Respondent to cth factor, da,c represents the factor scorecoefficient of a

thperformance index for c

thfactor, Wb,a represents the standard score of b

thRespondent for

ath

performance index and x represents the population of the sampled Respondents. W b,a is estimated

from:

where A represents the allowable minimum raw score for the performance index; in this instance, it is 1;

pb represents the raw score of bth

performance index; qb represents the mean of the raw scores of bth

performance index by the sampled Respondents; eb represents the standard deviation of the raw scores

of bth

performance index by the sampled Respondents.

Given that the standard scores by the bth

respondent in the thirty six variables under consideration are

Wb,1, Wb,2, Wb,3 . . . , Wb,36, then the performance of ICT based on the view of each respondent on the six

extracted factors are denoted by M1 M2, M3, M4, M5 and M6 are defined as follows:

M1= 0.081Wb,1 + 0.091Wb,2 + + 0.008Wb,36 (4)

M2= 0.058Wb,1 + 0.034Wb,2 + + 0.063Wb,36 (5)

M3= -0.021Wb,1 + 0.019Wb,2 + + 0.008Wb,36 (6)

M4= 0.130Wb,1 + -0.006Wb,2 + + -0.062Wb,36 (7)

M5= 0.024Wb,1 + -0.009Wb,2 + + 0.088Wb,36 (8)

M6= 0.010Wb,1 + -0.023Wb,2 + + 0.251Wb,36 (9)

Table 7 shows the calculated percentage contributions of each of the first twenty sampled respondents to

each of the six factors. It is revealed that respondent described with identity Res5 has highest contribution

of 5.6382 (5.73%) to factor 1 while sampled respondent described with identity Res8 has the highest

contribution of 4.0261 (6.36%) to factor 2. Similarly, sampled respondent described with identity Res19

has highest contribution of 2.2452 (7.34%) and 3.7065 (6.42%) to factors 3 and 4 respectively. Finally,sampled respondents described with identity Res1 has the highest contribution of 3.7206 (7.29%) to

factor 5 while sampled respondents described with identity Res12 has the highest contribution of 6.2826

(7.32%) to factor 6.

Table 7: Aggregate factor scores with percentage contributions for the first twenty respondentsFactor 1 Factor 2 Factor 3 Factor 4 Factor 5 Factor 6

Score % Score % Score % Score % Score % Score %

Res1 3.3931 5.35 2.8545 4.51 1.7395 5.69 2.3820 4.12 3.7206 7.29 3.6125 4.21

Res2 3.1861 5.02 2.8605 4.52 1.3035 4.26 2.6700 4.62 3.0996 6.08 3.7825 4.41

Res3 3.2642 5.14 2.7758 4.38 2.0442 6.68 3.2325 5.6 3.4114 6.69 3.7843 4.41

Res4 2.5842 4.07 3.1558 4.98 1.7332 5.67 3.0485 5.28 2.4144 4.73 4.8873 5.70

Res5 3.6382 5.73 3.4689 5.48 1.2512 4.09 3.1845 5.51 3.0364 5.95 3.9443 4.60

Res6 3.5282 5.56 3.2708 5.16 0.4092 1.34 2.8435 4.92 2.6504 5.20 4.2253 4.92

Res7 3.3732 5.32 3.1378 4.95 1.4262 4.66 2.9615 5.13 2.6724 5.24 3.8273 4.46

Res8 3.4814 5.49 4.0261 6.36 1.1418 3.73 2.5692 4.45 2.1631 4.24 4.5630 5.32Res9 3.1182 4.91 3.2698 5.16 1.4642 4.79 3.2595 5.64 2.1274 4.17 4.0073 4.67

Res10 2.8632 4.51 3.2076 5.06 1.5342 5.02 2.6775 4.64 2.4444 4.79 4.3223 5.04

Res11 3.1022 4.89 3.4838 5.5 1.8252 5.97 2.7075 4.69 1.4974 2.94 4.5313 5.28

Res12 3.0355 4.78 3.4695 5.48 2.0505 6.71 3.4130 5.91 2.5528 5.01 6.2826 7.32

Res13 3.3344 5.25 3.4901 5.51 1.7578 5.75 2.4142 4.18 1.2251 2.40 4.8180 5.60

Res14 3.4732 5.47 2.9668 4.68 1.2522 4.09 3.3115 5.73 2.3724 4.65 4.9973 5.82

Res15 3.3222 5.24 2.9566 4.67 1.3742 4.49 2.4405 4.23 2.0834 4.08 4.6103 5.37

Res16 2.4432 3.85 2.7358 4.30 1.0482 3.43 2.3525 4.07 1.2984 2.55 3.9523 4.61

Res17 3.3751 5.32 2.9505 4.66 1.8065 5.92 2.5400 4.41 3.6526 7.16 3.5455 4.13

Res18 3.1501 4.96 3.0525 4.82 1.4375 4.7 2.9860 5.17 2.9636 5.81 3.6485 4.25

Res19 3.2102 5.06 3.0638 4.84 2.2452 7.34 3.7065 6.42 3.2074 6.29 3.5833 4.18


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In a bid to evaluate the percentage contributions of each factor to the current performance of ICT in the

universities, the eigenvalues and percentage variance of each factor shown in Table 8 is generated.

Table 8: Eigenvalue of factors

Component

Initial Eigenvalues

Total % of Variance Cumulative %

1 10.481 29.114 29.114

2 5.098 14.162 43.275

3 3.091 8.586 51.861

4 2.707 7.518 59.379

5 2.304 6.400 65.779

6 1.747 4.854 70.633

The percentage contribution of each factor is denoted by PC and is formulated as follows:

where P is the number of performance indices, FC is the eigenvalues and M i,j represents the loading of jth

factor on ith

performance index. The eigenvalues, which are the sums of squares of factor loadings, are

used to indicate how well each of the extracted factors fits the data from the sample population.

It is shown in Table 10 that the four factors contributed 69.86% of the current performance of ICT in the

Nigerian universities. Factor 1 described as Communication and Feedback contributes 33.37% out of69.86%. This achievement is attributed to the fact that several universities in Nigeria provide facilities

such as Radio and Television which help in no small measure to run free flow communication systems.

The strong Global Systems for Mobile (GSM) communication in and around the neighbourhood of the

universities is another reason. The substantial contributions of Communication and Feedback reveal

that many university systems will fail or suffer to achieve their set goals if effective and realizable ICT

based communication and feedback systems are not put in place. Factor 2 described as Study Aid

contributes 14.64% of the total contribution. This shows that ICT is important for qualitative study,

research and knowledge impartation. The contribution of this factor would have been higher but for the

fact that most universities in Nigeria lack sufficient internet and other related facilities for the study needs

of students. Where they are available, they offer poor quality and non-affordable services. Factor 3

named as Processing and Administration contributes 11.4% to the performance of ICT in theuniversities. This suggests the necessity of ICT for smooth administration which is supportive to efficient

admission processing, course registration, processing and checking of results and maintenance of

financial records. Relationship and Management which is factor 4 contributes a total of 10.45% to the

performance of ICT in the Nigerian universities. This exhibits the usefulness of ICT as a tool for good

management which is important for campus peace and establishment of linkages with relevant bodies or

agencies. The remaining 30.14% is considered as the expected contributions of some extraneous factors

that are important but their related performance indices were not considered in the research. Such

extraneous factors include but nor restricted to training, security of lives and properties, discipline among

Res20 2.5842 4.08 3.1558 4.98 1.7332 5.67 3.0485 5.28 2.4144 4.73 4.8873 5.7

Total 63.461 100 63.353 100. 30.5785 100 57.749 100 51.0076 100 85.813 100


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students and staff, curriculum and government policy on ICT. The following are typical performance

indices that were not considered.

a. Impact of ICT on campus security

b. Impact of ICT on acquisition and procurementc. Impact of ICT on internally generated revenued. Impact of ICT on staff recruitment, promotion and disciplinee. Impact of ICT on students assessment and grading f. Impact of ICT on prevention and management of campus hazardsg. Government policies on ICT in the university systemh. Government funding of ICT projectsi. Adequacy of the university curriculum on ICT based courses

j. Competency of the management staff on the use of ICT facilitiesk. Competency of the ICT staff and professionals

CONCLUSION

Nigerian universities have continued to perform poorly in the web ranking of the world universities. One of

the reasons attributed to this is their poor state of ICT. The not too impressive attitude of government

towards empowering the universities through strong financing of ICT projects easily comes to the fore.

Most universities lack stable power supply which is an essential ingredient for implementing stable ICT

systems. This constitutes stumbling blocks to smooth internet operations and access. It also hinders

sound teaching and research. In this research efforts have been directed towards the determination of the

contributions of some factors (based on indices freely formulated by the researchers) to the current level

of the performance of ICT in the Nigerian universities with attendant measures for its improvement.

Factor analysis by principal components has been used for the evaluation of the performance index of

ICT. Four factors were extracted and each of them loaded on some related performance indices. The

initial component matrix generated was subjected to orthogonal transformation with a view to discover

reasonable factorization of the performance indices. Factor score coefficient matrix was also generated to

serve as basis for determining the degree or extent of soundness of the assessment of every respondent.

The eigenvalue of each factor was calculated and used for the evaluation of the percentage contribution

of each factor to the current performance of ICT in the universities. The percentage contribution of the

four extracted factors was less than 100. This shows that the related performance indices of some

extraneous (latent) factors that play significant roles where left out in the administered questionnaire. The

results obtained placed high premium on the active use of ICT as tool for communication, feedback,

study, processing, administration, relationship and management within the universities. These results

corroborated the positions held in Wescott et al (2007) and Bach et al (2011) that ICT is a practical tool

for service delivery and management. The results equally agreed with the conclusion drawn in Akinyokun

et al (2011) that ICT is a tool for proper planning, monitoring, implementation and management in any

system for active participation of community of users. For the sustenance of these results, issues like

active and adequate funding and monitoring of ICT projects, engagement of qualified and competent ICT

professionals, politically stable and peaceful operational environment, good electricity supply, ICT

oriented curriculum among others are very essential ingredients that need adequate attention of


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government and university managements for increasing contributions from ICT to the Nigerian university

system.

In principle, there are many corporate organizations in Nigeria who should assist government in financing

ICT projects in the universities. A very strong monitoring, control and policing system could be put inplace to ensure that the purposes of their assistants are achieved. The focus of the future research is to

increase the number of the performance indices so as to extract more factors and perhaps increasing the

contributions of the factors extracted in this work. Attempt will also be made to work with completely

different set of performances indices with a view to determine if same or different factors will be extracted.

paper on lg

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