Monitoring intensity-and-procurement-performance-emprical-evidence-from-elgeyo-marakwet-county-kenya

International Journal of Scientific and Technological Research (IJSTER)
ISSN: 2617-6416 Vol. 1 (1) 97-108 November, 2018
www.oircjournals.org
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Tallam and Kibet (2018) www.oircjournals.org
Monitoring Intensity and
Procurement Performance; Empirical
Evidence from Elgeyo Marakwet
County, Kenya.
Lonah Kandie Tallam & Kibet Yusuf
Jomo Kenyatta University of Agriculture and Technology
Type of the Paper: Research Paper.
Type of Review: Peer Reviewed.
Indexed in: worldwide web.
Google Scholar Citation: AIJMR
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How to Cite this Paper:
Tallam, L. K. and Kibet, Y., (2018). Monitoring Intensity and Procurement Performance.
Empirical Evidence from Elgeyo Marakwet County, Kenya. International Journal of Scientific
and Technological Research (IJSTER), 1 (1) 97-108.

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Monitoring Intensity and Procurement Performance.
Empirical Evidence from Elgeyo Marakwet County,
Kenya.
Lonah Kandie Tallam & Kibet Yusuf
Jomo Kenyatta University of Agriculture and Technology
Abstract
Contract management practice is a vital aspect
in any organization that intends to gain a
competitive advantage and value for money. In
public organizations, every year a major
portion of budget allocation is given for
procurement of goods and services for various
kinds of projects to be done. The study focused
on the effect of monitoring intensity on
procurement performance of public
organizations in Elgeyo Marakwet County.
The study was guided by relational contract theory and principal-agent theory. It adopted a descriptive study
design utilizing questionnaires as the primary data collection tool. The staff from finance and procurement
departments in the County government formed the study’s unit of analysis. The sample for the study was
procurement officers and finance officers. It also adopted census sampling on all the target respondents. A pilot
study was done in Uasin Gishu County Government. The computer programme Statistical Package for Social
Sciences (SPSS) version 22.0 aided in data analysis. Data was analyzed using Quantitative data analysis with
both descriptive and inferential statistics. Descriptive statistics like frequencies, percentages, means and cross
tabulation will be used while multiple regressions will be used to test the hypothesis. Presentation of finding done
using questionnaires which was coded, organized, analyzed and presented using frequency tables, and
percentages. The study found that the organization was able to practice monitoring intensity with the view to
enhance procurement performance. The results established a positive but weak correlation between the variables
(P= 0.288, r=.057). The strength of association was weak. The study concluded that monitoring intensity was a
factor that influences procurement performance in organizations. However it was noted that other factors were
needed to support this practice. It was recommended that contractors should be allocated with the right amount
of resources to complete the projects assigned to them.
Introduction
Contract management is the process that ensures
both parties to a contract fully meet their respective
obligations as efficiently and effectively as possible,
in order to deliver the business and operational
objectives required from the contract and in
particular to provide value for money. As a result
developing and managing contracts is a skill
required by public sector entities in the management
of the majority, if not all, programmes. However,
contract management is not an end in itself and it is
important that all contracting decisions and actions
focus on the outcomes that entities are seeking to
achieve (Kakwezi, 2012).
In the public sector there is huge variety of contracts,
with different types of contracts needing different
types of contract management. On the other hand
agency contract management is the process of
managing all stages in the lifecycle of enterprise-
wide contracts with the goal of minimizing costs and
risks, maximizing revenues, streamlining
operations, and improving compliance with policies,
procedures, regulations, and negotiated terms and
conditions (Saxena, 2008).
Procurement performance has been described as the
degree of achievement of certain effort or
undertaking. It relates to the prescribed goals or
objectives which form the project parameters
(Chitkara, 2015). In order to achieve optimum
procurement performance, procuring entities
through the existing legal framework are required
to firstly consolidate departmental procurement
plans to provide the entity’s corporate procurement
plan which before its implementation must get the
accounting officer’s approval. Industry Manual,
(2008) indicates that a procurement plan is an
instrument for implementation of the budget and
should be prepared by the user departments with
ARTICLE INFO
Received 1st October, 2018
Received in Revised Form 29th October, 2018
Accepted 1st November, 2018
Published online 2nd November 2018
Key words: Monitoring Intensity, procurement
performance, Contract Management

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a view to avoiding or minimizing excess votes in
the entities’ budgets and to ensure that procurements
do not proceed unless there are funds to pay for
them. This implies that all procurement plans must
be well integrated into the budget process based on
the indicative budget as appropriate and in
compliance with the procurement law.
Globally, today governments all over the world have
received a great deal of attention as providers of
essential services such as health, education, defense
and security, and infrastructure (OECD, 2000). So
as to be able to meet the demand of all these services,
governments procure goods, works and services
from supply markets. That means public sector
procurement has both economic and political
implications. There is no doubt amongst policy
makers, managers, professionals and academicians
about the role of public sector procurement in
facilitating government operations towards
economic growth, poverty reduction and good
governance through provision of quality services to
the citizens. The performance of public procurement
markets has significant implications for the
effectiveness of governance in both developed and
developing countries. There are strategic decisions
to be made that will affect the nature of contract
management role. For example, one might contract
out a whole requirement leaving one a relatively
straightforward contract management task (OECD,
2005).
In Africa, South Africa in particular, the Common
Market for East and Southern Africa
(COMESA,2011) guidelines observes that neither
the COMESA Procurement Directive, nor the
UNCITRAL Model Law, specifically address the
subject of contract management. Despite the
importance of contract management researchers are
unable to empirically and systematically pinpoint
the determinants and constraints by using objective
‘hard data’ (Jiang & Qureshi, 2006). In several
countries, few articles have rigorously analyzed and
empirically tested the factors that actually affect a
government agency’s decision to manage contracts.
Within the relatively scarce empirical evidence on
contracting decisions and management (Boyne,
1998; Ferris & Graddy, 1986), there is yet little
information on the effectiveness of contract
management specific to public procurement.
In East Africa, Uganda for example, contract
management has become a megatrend in many
public entities especially as result of social
accountability and increased demand of service
delivery by citizens (World Bank Institute, 2011;
Schiel, 2007; Swinnery & Netssins, 2007).
However, Dew (2008); Thai (2005) and Bolton
(2006) observe that contract management challenges
in both public and private organizations are endemic
in any contractual relationship due to lack of
transparency and poor record keeping. Successful
contract management and completion is often
defined, as procurement of the right item, in the right
quantity, for the right price, at the right time, with
the right quality, from the right source (Thai, 2005).
Prager (1994) contends that proper and effective
management and monitoring of contracts helps
improve the quality of goods and services and
reduces procurement cost thus achieving three broad
goals: quality products and services, timely delivery
of products and services, and cost effectiveness
(within budget).
Currently, Kenya loses billions of taxpayers’ money
to improper procurement process, specifically poor
contract management practices. This commonly
happens in the country’s state corporations due to
issues, such as, corruption, litigations, contract
cancellations and substandard service or product
delivery. This calls for the pressing need to make
appropriate policies and decisions to save the
situation. Since the state requires to realize its value
for money in the process of the serving its people,
every state corporation is required to account for its
expenses (Contract Monitoring Kenya Network,
2012). Therefore, contract management is a valuable
step in public procurement as it ensures that service
or products delivery is undertaken as per the
contractual terms and conditions.
Statement of the Problem
In County Governments, every year a major portion
of budget allocation is given for procurement of
goods and services for various kinds of projects to
be done. However in some organizations,
procurement has not been done the right way.
Proponents argue that contracting can reduce costs
and improve flexibility and customer satisfaction.
Critics point to a growing number of failed
contracts, arguing there are numerous pitfalls
associated with contracting. The problem arisen due
to poor contract management leading to failure to
procure the right quality goods, in the right time at
the right price. It was reported that 80 to 90% of the
goods are not managed properly. Therefore there
was loss of government money which is not properly
addressed and many projects are not completed
(Kakwezi & Nyeko, 2010).
Despite efforts by public organizations being
transparent and accountable on what they procure,
the issue of poor performance is still felt. The county
governments still lose billions of taxpayers’ money
to improper procurement process, specifically poor
contract management practices.

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Numerous studies have been done on contract
management but little has been done in Kenya and
specifically in County Governments of Kenya.
Outside Kenya, Holtand Graves (2001) conducted a
study on benchmarking UK public procurement
performance, Bassioni, Price and Hassan (2004)
dwelt on the performance measurement in
construction industry. Moreover, Jeanette (2008)
conducted a study on the benchmarking and its
importance on procurement performance. It is
therefore against this problem and gap that the study
seeks to assess contract management practices and
procurement performance in County Governments
of Kenya, a case of Elgeyo Marakwet County.
Research Objective
To determine the effect of monitoring intensity on
procurement performance of Elgeyo Marakwet
County, Kenya.
Research Hypothesis
H01. There is no significant effect of monitoring
intensity on procurement performance Elgeyo
Marakwet, County.
Literature Review
Theoretical Review
The study was guided by relational contract theory.
Relational Contract Theory
Relational Contracts Theory is a theory mainly
developed by Ian MacNeil in U.S.A. in 1980.
According to relational contracts theory, relations
are governed by a set of common characteristics
(norms) that play an important role, regarding the
content of the relation, the formation of parties’
obligations and the actual operation of the contracts.
These norms are based on a set of internal values and
the broad context social and economic factors,
related to the relation. According to MacNeil, there
are ten norms common for all kinds of contracts: role
integrity, reciprocity, implementation of planning,
effectuation of consent, flexibility, and contractual
solidarity, the ‘linking norms’ (restitution, reliance
and expectation interests), creation and restraint of
power, propriety of means and harmonization with
the social matrix. There are also five norms
(additional or the same as these of common
contracts), responding in an intensive way to
contracts with a highly relational character than
conventional contracts: role integrity, preservation
of the relation (expansion of contractual solidarity),
harmonization of the relational conflict,
supracontract norms and propriety of means.
This theory is applicable in the study variables as
contracts in the county government need integrity,
reciprocity, planning, flexibility among other norms
to be successful, hence enhance procurement
performance. This may be a result of an
overemphasis on the existence of collaborative
relationships and social control mechanisms and
is a reflection of the observation that, even where a
written contract exists, frequently companies seek
to avoid the use of legal action against their
suppliers and or customers. Yet, empirical
investigations reveal the existence of detailed
contracts that firms use to manage their firm
relationships. Indeed, empirical research into
manufacturer retailer networks as well as into
manufacturer to manufacturer relationships shows
that companies attempt to simplify and facilitate
the complex process of a business interaction by
embracing a new form of contract described as
umbrella agreements. It informs the study variables
of monitoring intensity practice and risk
management practices as it emphasizes on planning
and the management of contracts in organizations.
Macneil’s theoretical criticism of this view of
contract is that it does not take into account the
co-operative, relational phenomena to which he
draws the attention. As well as taking up the
social philosophical issues involved in this, he
makes this point in respect of many contract
doctrines, such as the regulation of penalty
clauses (1981b) and (other) standard terms
(Macneil, 1984), the adjustment of formally strict
liabilities (Macneil 1983b) and the nature of
breach. The last of these is particularly instructive,
for it does not turn on any welfares considerations
but solely on “economic efficiency.”
Effect of Monitoring Intensity and Procurement
Performance
Brown and Hyer (2010), describe monitoring as the
tracking aimed at identifying variances from the
original plan using simple checklist to sophisticated
dashboard style approaches. According to Meredith
and Mantel (2012), cost (budget) and scope
(performance) and time (schedule), are important
things to be considered during planning, and should
therefore be monitored and controlled effectively.
Until the project is complete the cycle of planning,
monitoring and exercising control should be made a
routine. The organization structure should construct
the process as an integral part ensuring that it does
not cause any conflicts. The organization should
clearly outline the aspects for monitoring and
control bearing in consideration the scope,
boundaries, time and cost. During the life of a
project the team in charge of monitoring should
develop appropriate approach for monitoring the
Key Performance Indicators (KPI’s). According to
Brown and Hyer (2010) the concept of project
control is a combination of decisions, procedures,
decisions and actions included in coping with the

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project variances. Project control therefore acts as a
guide to the firm and influences the decisions on
when to make changes or focus on the project
course.
According to Brown and Hyer (2010) in their view
to monitor and control contracts assert that several
issues interfere with project execution causing the
actual/real performance to deviate from the
budgeted performance. The issues are: (i) Scope
Creep; which basically refers to a situation where the
project grows beyond its initial size. This may be
caused by new government rates that will influence
way leaves causing the customers’ needs to inflate
the budget (ii) Murphy’s Rule; which asserts that
you cannot be accurate and anticipate all risks. The
government may decide to construct new roads
where already there is an existing fiber cableen
trenched; the relocation of such a network was not
anticipated and would be costly.(iii) Pareto’s
principle; which states that 80% of project’s
limitations and postponement are caused by 20% of
project actions. Red tape in organizations may lead
to delays intake-off of projects. (iv) Increase of
Commitment principle which holds that, people
persist in engaging in failing course of action even
at the state of fallacy intent. Therefore a procurement
service level agreement monitoring initiative can
have a strong influence on decisions to escalate or
de-escalate commitment
2.4 Conceptual Framework
The study was guided by the following conceptual
framework. The dependent variable is procurement
performance while the independent variables are the
contract management practices.
Independent variables Dependent variable
Figure 2.1: Conceptual Framework
Research Methodology
Research Design
This study used descriptive case study design.
According to Sekaran & Bougie (2011) descriptive
study is undertaken in order to ascertain and be able
to describe the characteristics of the variable of
interest in a situation. Descriptive studies are
essential in many situations especially when using
qualitative and quantitative data in understanding
the phenomena.
Population
According to Kumar (2008), populations are all the
items in the field of inquiry. The population of the
study comprised of all the employees of the finance
and procurement departments of the County
Government of Elgeyo Marakwet. According to the
County’s 2018 records there are 31 procurement
employees and 29 finance employees. This formed
the target population of the study. This is distributed
as shown in Table 3.1
Table 3.1: Population
Department Population
Finance department 29
Procurement department 31
Total 60
Sample and Sampling Technique
The study was stratified the population to their
departments. It then used census sampling to select
the respondents who participated in the study in this
case all the population under the study participated
in the study. According to Rosseau (2012), a census
is an attempt to gather information about every
individual in a population. Census sampling is
normally used when the population is small and
manageable. The sample size therefore was 60
respondents.
Table 3.2: Sample Frame
Department Population Sample size
Finance department 29 29
Procurement department 31 31
Total 60 60
Monitoring intensity practice
 Compliance to specifications
 Complaints management
 Utilization of resources
Procurement performance
- Quality projects
- Lead time management
- Efficiency and effectiveness
- Delivery of goods

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Data Collection Method
The study used questionnaires to collect primary
data. The questionnaires were semi structured
questionnaire. The open ended questions were used
in order to allow respondents to provide information
which they may deem relevant for the study. Closed
ended questions were used in order to standardize
the responses and save on the respondents’ time
taken to fill in the questionnaire. The researcher will
exercise care and control to ensure all questionnaires
issued to the respondents are received.
Data Collection Procedure
The researcher acquired a permit from Jomo
Kenyatta University of Agriculture and Technology;
the researcher sought permission from the County
Government to conduct the research. A research
permit from the Ministry of Education, Science and
Technology (NACOSTI) was then sought. After
getting all the requirements the researcher embarked
on the journey of collecting data starting from
familiarizing herself with the target population to
issuing of the questionnaires and collecting them at
an agreed later date. Follow ups were made to ensure
that all the questionnaires are filled and returned.
Pilot Test
The researcher conducted a pilot study to ascertain
the reliability of the instruments before the study
was done. A pilot study was done in Uasin Gishu
County government which had similar
characteristics as the area of study. Reliability is the
degree to which tests agree with itself and free from
random errors which normally occur through
chance. As random error in the data decreases,
reliability of the data increases (Mugenda, 2008). In
order to ascertain the reliability of the research
instruments, the results from the pilot study were
subjected to Cronbach Coefficient Alpha. The
reliability coefficient reflects the extent to which
items measure the same characteristics. Coefficient
Alpha is calculated using the variance of the total
test score and the variance of the individual item
scores. Correlations achieved here would be
expected to be above 0.7 to signify a high reliability.
A reliability index of 0.7 was appropriate as
Mugenda & Mugenda (2009) stated that a
correlation coefficient tells the researcher the
magnitude of the relationship between the two
variables, the bigger the coefficient, the stronger the
association between the two variables.
Validity of the Research Instruments will also be
tested. Face and content validity of the questionnaire
was tested whereby face validity is in relation to the
misunderstanding or misinterpretation of the
questions in the questionnaire. This was checked by
employing the pre-testing method. Content validity
on the other hand refers to the capacity of the
instrument to provide adequate coverage of the
topic. Adequate preparation of the instruments under
the guidance of the experts and pre-testing of open
ended questions helped in establishing content. The
questionnaire was assessed by the supervisor in
order to make sure the information in the instrument
was valid.
Data Processing and Analysis
After data collection, the researcher coded the items
ready for analysis. The computer programme
Statistical Package for Social Sciences (SPSS)
version 22.0 aided in data analysis. Data was
analyzed using quantitative data analysis with both
descriptive and inferential statistics. Descriptive
statistics like frequencies, percentages and means,
cross tabulation were used.
Pearson moment of correlation was used to find the
correlation between the variables. Multiple
regression analysis with ANOVA technique was
used to determine the effect of independent variables
on the dependent variable, it was used to measure
the relative influence of each independent variable
based on its covariance dependent variable and was
useful in forecasting. Usually, it is most appropriate
when both the independent and dependent variables
are interval, though some social scientists also use
regression on ordinal data. Like correlation,
regression analysis assumes that the relationship
between variables is linear. In its simplest form
multiple regression analysis involves finding the
best straight-line relationship to explain how the
variation in an outcome (or dependent) variable, Y,
depends on the variation in a predictor (or
independent or explanatory) variable, X. Once the
relationship is estimated, it is possible to use the
equation:
Y = b0 + b1X1 + ɛ
Where:
X1 Represents monitoring intensity
Y Represents The Dependent variable
(Procurement performance)
b Represents Independent Variable
Coefficients
ɛ Represents Error term (sum of the deviations
within the regression line)
Research Findings and Discussion
Response Rate
A total of 60 questionnaires were sent out to the
respondents to fill. Of these questionnaires, 52 were

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returned for analysis. The returned 52 questionnaires
accounted for 86.6% response rate. A response rate
of 70% and above is adequate (Mugenda and
Mugenda, 2013) and therefore a response rate of
86.6% was acceptable for data analysis. Table 4.1
shows the response rate.
Table 4.1: Response Rate
Category Frequency Percentage
Administered 60 100.0 %
Returned 52 86.6%
Reliability Test Results
Before the actual study, the researcher did a pilot test
to ascertain the reliability of the research
instruments. Data was subjected into cronbach alpha
coefficient and the findings were generated in
relation to each variables (see Table 4.2).
Table 4.2 Reliability Statistics
Variable Cronbach Alpha Coefficient Test item
Monitoring intensity .866 5
Risk management .857 6
Evaluation .866 6
Dispute Resolution .734 7
According to the reliability statistics indicated the
results shows that the research instrument is reliable.
A Cronbach alpha coefficient of >0.7 is deemed
excellent reliability (Rousson, Gasser & Seifer,
2010).
Demographic Characteristics of the
Respondents
An inquiry was made on the ages of the
demographics of the respondents, among the
demographic information sought were; gender, age,
academic level and work experience. These
variables were considered to have an influence on
the performance of procurement operations in
organizations.
Gender of the Respondents
An inquiry was made on the gender of the
respondents. Table 4.3 showed that 55.8% (29) were
female while 44.2% (23) were male. It was
established that majority of the respondents were
female as illustrated in Table 4.3
Table 4.3 Gender of the Respondents
Gender Frequency Percentage
Male 23 44.2
Female 29 55.8
Total 52 100
Age of the Respondents
The study assessed the age of the respondents. Age
was further categorized into different groups. The
study established that majority 32.7% (17) of the
respondents were between the ages 31 to 35 years,
21.2% (11) were between 26 to 30 years, another
21.2% (11) were between 36 to 40 years, 15.4% (8)
were 41 to 45 years and 9.6% (5) were over 46 years.
The results therefore are illustrated in Table 4.4;
Table 4.4 Age of the Respondents
Age Frequency Percentage
26-30 Years 11 21.20
31-35 Years 17 32.7
36-40 Years 11 21.2
41-45 Years 8 15.4
Over 46 years 5 9.6
Total 52 100
Level of Education
The level of education of the respondents was also
sought; the findings indicated that the respondents
had diverse levels of education, majority had a
masters level of education 36.5% (19), 32.7% had a
degree level of education 32.7% (17), 26.9% (14)

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had a diploma level and the least of 3.8% (2) had a
technical certificate. The study shows a high
percentage of the respondents had completed their
masters’ levels followed by degree level and
therefore they were learned and well versed on the
study. Table 4.5 illustrates the findings.
Table 4.5 Level of Education
Level of education Frequency Percentage
Technical certificate 2 3.8
Diploma level 14 26.9
Degree level 17 32.7
Masters level 19 36.5
Total 52 100
Work Experience of the Respondents
The study sought to establish the level of work
experience of the respondents. The results showed
that majority 36.5% (19) of the respondents had
worked for 5 to 10 years, followed by 28.8% (15)
who had worked for between 2 to 5 years and 11
years and above respectively, the least 5.8% (3) had
worked for less than 1 year. The findings are
illustrated in Table 4.6;
Table 4.6 Work Experience of the Respondents
Work experience Frequency Percentage
Less than a year 3 5.8
Between 2-5 years 15 28.8
Between 5-10 years 19 36.5
11 Years and above 15 28.8
Total 52 100
Descriptive Statistics
In this section descriptive analysis of the objective
of the study was done. A scale of 1 to 5 was used to
show the extent to which the respondents agreed to
the statements of effects of monitoring intensity, risk
management, evaluation practices and dispute
resolution practices on procurement performance.
Effects of Monitoring Intensity Practice on
Procurement Performance
For analysis of objective one, correlation was the
preferred statistic. This statistic helped to find out
the relationship between variables. The analysis
therefore opens with the descriptive statistics
(frequency, percentage and mean distribution) for
the level of agreement on a five point Likert scale of
the variable performance (Table 4.7).

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Table 4.7 Monitoring Intensity and Procurement Performance
Monitoring Intensity SA A U D SD MEAN
i The contractors follow the standards
required for the their methods of
contracting
F 15 30 2 4 1 4.039
% 28.8 57.7 3.8 7.7 1.9
ii The contractors always do the right
amount of work within the
approximated time
F 17 28 0 3 4 3.981
% 32.7 53.8 0 5.8 7.7
iii The contractors always use the right
amount of resources to complete the
projects assigned to them
F 4 36 5 4 3 3.654
% 7.7 69.2 9.6 7.7 5.8
iv The supervisors carry out their duties
to make sure that the contracts given
out are successful
F 16 27 3 4 2 3.981
% 30.8 51.9 5.8 7.7 3.8
v Funds allocated are well utilized for
only the intended projects
F 25 18 5 2 2 4.192
% 48.1 34.6 9.6 3.8 3.8
vi Formal monthly inspections are being
done on the projects
F 22 21 6 3 0 4.192
% 42.3 40.4 11.5 5.8 0
vii The contractors always comply with
the service quality levels which has
been specified in the bidding
document
F 10 35 0 0 7 3.789
% 19.2 67.3 0 0 13.5
The responses on monitoring intensity revealed that
the contractors follow the standards required for the
their methods of contracting where 57.7% agreed on
this and 28.5% strongly agreed giving an average
mean of 4.03. On the response that the contractors
always do the right amount of work within the
approximated time, the study established a high
percentage of agreement on this 53.8% agreed while
32.7% strongly agreed with a mean of 3.98.
Further results showed that a majority 69.2% agreed
and 7.7% strongly agreed that the contractors always
use the right amount of resources to complete the
projects assigned to them. The mean was labeled at
3.6538. In addition, the study established that
majority of the respondents agreed 51.9%, 30.8%
strongly agreed that the supervisors carry out their
duties to make sure that the contracts given out are
successful, this was spread at 3.9808.
The findings also indicated that funds allocated are
well utilized for only the intended projects with
majority 48.1% of the respondents strongly agreeing
on this and 34.6% agreed. The mean was spread at
4.1923. Further findings on the fact that formal
monthly inspections are being done on the projects
indicated a majority of the respondents being in
agreement with this. This was denoted by 42.3%
strongly agreed while 40.4% agreed with a mean of
4.1923.
Lastly, the findings showed that majority of 67.3%
of the respondents and 19.2% agreed and strongly
agreed respectively on the idea that the contractors
always comply with the service quality levels which

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has been specified in the bidding document. The
mean was spread at 3.7885.
Inferential Statistics
Correlation analysis was used to determine the relationship between variables, while regression analysis was
used to test the hypothesis of the study.
Correlation Analysis on Monitoring Intensity and Procurement Performance
This was done using Pearson correlation statistical analysis. The correlation was measured at 0.05 significant level
(2-tailed). The findings are shown in table 4.8.
Table 4.8 Correlation Analysis Monitoring Intensity and Procurement Performance
Monitoring Intensity
Performance Pearson Correlation 0.057**
Sig. (2-tailed) .288
N 52
**. Correlation is significant at the 0.05 level (2-tailed).
Pearson's correlation was run to determine the
relationship between the monitoring intensity and
procurement performance of the organization. The
results established a positive but weak correlation
between the variables (P= 0.288, r=.057). The
strength of association was weak.
From the Analysis report p = 0.288, which is more
than 0.05, as such, there is no significant relationship
between monitoring intensity and the procurement
performance of the organization at Elgeyo
Marakwet County. Therefore, monitoring intensity
alone could not be associated with high procurement
performance of the organization.
Hypothesis testing using Regression Analysis
Table 4.9 Model Summary
Model Summary
Model R R Square Adjusted R Square Std. Error of the
Estimate
1 .923a
.852 .849 .57938
a. Predictors: (Constant), d, a, b, c
This table provides the R and R2
values. The R value
represents the simple correlation and is 0.923 (the
"R" Column), which indicates a high degree of
correlation. The R2
value (the "R Square" column)
indicates how much of the total variation in the
dependent variable, procurement performance, can
be explained by the independent variable, contract
management practices. In this case, it is 85.2%
which is very large.
Table 4.10 ANOVA Summary for Regression Model
ANOVAa
Model Sum of Squares df Mean Square F Sig.
1 Regression 439.053 4 109.763 326.982 .000b
Residual 76.536 228 .336
Total 515.589 232
a. Dependent Variable: Procurement performance
b. Predictors: (Constant), d, a, b, c
The prediction of the variable p represented by 0.000 indicates that the regression model is statistically
significant.
Table 4.11 Model Summary
Coefficientsa
Model Unstandardized Coefficients Standardized
Coefficients
t Sig.
B Std. Error Beta
(Constant) 1.944 .619 3.139 .002

107 | P a g e
Monitoring intensity -.017 .011 -.043 -1.559 .120
From the regression model computed in Table 4.11,
the research hypotheses were tested using the
significance level of the coefficients. The research
aimed to test the hypothesis with an aim of accepting
or rejecting the relationship between contract
management strategies and procurement
performance. The research hypothesis for the study
included;
There is no Significant Influence of Monitoring
Intensity on Procurement Performance.
The regression results in Table 4.11 indicate that
monitoring intensity does not have a direct effect on
the procurement performance of the organization
with a beta coefficient of -0.043 and significance of
(p=0.120). The study accepted the hypothesis. These
findings imply that concentrating on monitoring
intensity does not give the organizations any bases
of procurement performance. This may be true in
that monitoring intensity should be incorporated
with other factors so as to influence the performance
of procurement operations of an organization.
Summary, Conclusions and Recommendations
Effects of Monitoring Intensity on Procurement
Performance
The first objective was to assess the effect of
monitoring intensity practice on procurement
performance. The study found that the organization
was able to practice monitoring intensity with the
view to enhance procurement performance, for
instance the organization made sure that funds
allocated are well utilized for only the intended
projects, they also did formal monthly inspections
on the projects to ensure progress and that the
contractors followed the standards required for the
their methods of contracting. Pearson's correlation
was also run to determine the relationship between
the monitoring intensity and procurement
performance of the organization. The results
established a positive but weak correlation between
the variables. The strength of association was weak.
Therefore, monitoring intensity alone could not be
associated with high procurement performance of
the organization.
The regression results in this variable indicated that
monitoring intensity does not have a direct effect on
the procurement performance of the organization.
The study accepted the hypothesis. The findings
implied that concentrating on monitoring intensity
does not give the organizations any bases of
procurement performance.
Conclusions
The study concluded that monitoring intensity was a
factor that influences procurement performance in
organizations. However it was noted that other
factors were needed to support this practice. The
county made sure that funds allocated are well
utilized for only the intended projects, they also did
formal monthly inspections on the projects to ensure
progress and that the contractors followed the
standards required for the their methods of
contracting.
Recommendations
On monitoring intensity practice, it is recommended
that contractors should be allocated with the right
amount of resources to complete the projects
assigned to them. On risk management practice, the
study recommends that there should be regular
supply of material resources to be used in projects,
this will allow them to manage the risks underway
as they complete the projects.
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