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Open Access Peer-reviewed

Beneficiary Needs Assessment on Implementation of Devolved Road Construction Projects in Kisumu East Sub-County, Kisumu County, Kenya

Sule George Aggrey Ochieng, Abuya Isaac Odhiambo
Journal of Business and Management Sciences. 2022, 10(1), 20-29. DOI: 10.12691/jbms-10-1-3
Received November 24, 2021; Revised December 29, 2021; Accepted January 07, 2022

Abstract

In Kenya, the potential for road improvements is enormous. The government has accelerated the construction of road infrastructure, resulting in a safer transportation system. There is a dearth of strong beneficiary monitoring measures to assist the implementation of road development projects and to promote accountability. As a result, it is clear that contract documentation does not take into account the requirement of beneficiary monitoring for effective implementation of roads construction projects. This loophole has contributed to challenges in implementation of road projects including scope creep, cost overruns, design issues, delay in land acquisition, and resettlement of project affected persons, shifting of utilities, very weak contract management and enforcement environment. The purpose of this study was to examine how beneficiary monitoring influences the implementation of county government devolved road construction projects in Kisumu east sub county, Kisumu county. The study’s objectives was; to assess the extent to which beneficiary needs assessment influences the implementation of County government devolved road construction projects in Kisumu East sub county, Kisumu county, Kenya. The study was based on a descriptive survey. The study's target population is 1100. The study used Krejcie and Morgan table to arrive at sample size of 285. Probability sampling was conducted using simple random sampling, while non-probability sampling was conducted using purposive sampling techniques. Self-administered questionnaires was used to collect data. To ensure validity and reliability of the research instruments, pilot testing was conducted using a sample of 29 respondents from Bondo Sub County, Siaya County. Cronbach’s alpha at α =0.80 was attained as the reliability coefficient of the pre-tested instruments for respondents piloted. Descriptive statistics applied included frequencies, percentages, mean, and standard deviation. Inferential statistics used correlation and Analysis of variance (ANOVA) to test for the hypotheses. hypothesis was tested at α=0.05 level of significance and the results was. There is no significant relationship between Beneficiary needs assessment and implementation of County government devolved road construction projects was rejected since P=0.000<0.05It is concluded that beneficiary needs assessment significantly influence implementation of devolved road construction projects. It is recommended that Kisumu East Sub County monitoring officers develops and implements a beneficiary needs assessment and visibility plan for enhancing sustainable implementation of devolved road construction projects in Kisumu East Sub County, Kisumu County.

1. Introduction

According to Hoogeveen & Taptué, 1, In the SAP and other projects after project selection phase, beneficial monitoring plays a major role. It enables the implementing agency to monitor and respond to any changes in attitudes of beneficiaries, or to unexpected alterations necessary to complete the project properly. The level of persons involved in the project is helpful to monitor. With regard to assessment, qualitative approaches employed in this approach can be utilized to measure the success of the project in responding to the requirements of communities and to gauge their project satisfaction.

The implementation of road construction projects has socio-economic benefits on a global scale. You can now transport passengers, raw materials and semi-finished and finished products that are meant to be sold using this technology. Which in turn spurs economic growth, creating jobs and improving the standard of living. Transportation around the world cannot be trouble-free without an extensive road network of superior quality. More money is spent on roads than on education, health, and social services put together. The implementation of road construction projects, on the other hand, is fraught with a number of difficulties. Scope creep, cost overruns, design issues, land acquisition delays, relocation of project affected persons, utility relocation, and a very weak contract management and enforcement environment are just a few of them.

1.1. Concept of Beneficiary Monitoring

Beneficiary monitoring is operationally defined in this study as a systematic investigation to monitor beneficiaries through beneficiary identification, beneficiary needs assessment, beneficiary involvement, beneficiary feedback and beneficiary satisfaction. The IFS/NS defines beneficiary monitoring as the systems investigation to monitor the views of the beneficiaries of an operation IFRC, 2. It is intended to provide managers with information on the recipient's reactions to the outcome of an operation and to show that progress is being made toward the operation. However positive, it should be noted that the reaction of the beneficiaries is only an improved proxy indicator of a situation to be created by an operation.

The focus of benefit monitoring is on access to and satisfaction with benefits by directly seeking feedback from females, men and kids that are the project target group. The transition from input to output is a matter of concern. It also gives managers an indication of progress in achieving the results of an operation. It employs a range of techniques and methods of data collection IFRC, 2.

According to the logic of beneficiary monitoring, if the members of a target group do not have access to operations outputs, they will not benefit, and if they do have access to operations outputs but choose not to use the results, they will not benefit at all (WFP). The beneficiary monitoring program tries to measure progress in the transition from service supply to benefits under the logical framework matrix (outcomes). Therefore, "leading indicators" are the indicators used in recipient monitoring. In the logical framework at outcome level, Beneficial Monitoring Indicators should be included. In this study, the leading indicators of beneficiary monitoring are five sub-independent variables. These key indicators include recipient identification, recipient requirements, recipient involvement, recipients' feedback and recipient satisfaction Hoogeveen & Taptué, 1.

Beneficiary monitoring requires a systematic study of recipient responses to operations outputs and activities and the different groups involved (men, women, boys, girls and other vulnerable groups). In the best case scenario, participatory qualitative methods are clearly identified with the nature of the surveillance investigations carried out by beneficiaries. Beneficial surveillance involves primary data collection almost always. Follow-ups are carried out in line with recipient reactions. Management can continue to implement the operation according to the plan. If problems are identified, a detailed investigation may be required for the management of the operation to be established (Hoogeveen & Taptué, 1).

1.2. Beneficiary Needs Assessment on Implementation of Devolved Road Construction Projects

Beneficiary Needs Assessment in this study is operationally defined as identifying the reasons a given project should be performed in a particular area. If you're interested in how the distribution of food goods for undernutrition prevention works, check out McLellan 3's study. Ready for Usage Foods (RUF) and its current indication for use were evaluated, as well as numerous publications and data supporting the use of RUF in the prevention of undernutrition. This concerns the study proposed in that the needs of the stakeholders and the beneficiary as general are being assessed for building projects. In this review, McLellan advocates for humanitarian actors and donor institutions to strongly support and empower sustainable interventions in the import and distribution of foreign solutions that are packaged in advance. He also recommends sustainable interventions to enable beneficiaries to progress rather than stagnation and empowerment and not to rely McLellan, 3.

In 2017 the USAID developed guidance to identify homes for orphans and vulnerable children in need of services. You noted there are several requirements for M&E reporting. Thus, M&E experts in these programmes, including for non-defined purposes, are prone to the development of broad-based tools which collect many types of information for multiple uses. This is a major strain on caregivers and results in inadequate and inadequate data utilization. This recognizes the need for a strong tool to assess the recipients' requirements to help improve the monitoring process for recipients. They recommended an information needs framework for orphans and the management and evaluation of vulnerable children's programs addressed this issue. It includes several types of information needs, highlights, methods, collection of information and the frequency of information collection.

1.3. Theoretical Framework

The study is guided on the following 3 theories:


1.3.1. Theory of Change

According to the fundamental logic, road development projects can lead to socioeconomic change in the targeted population. The theory of change is based on this fundamental logic. It was developed by Carol Weiss and popularized in 1995, and it claims that ineffectiveness of projected results is one of the key reasons why it is difficult to evaluate complex projects in the first place. Since it's not clear what mini-steps must be done in order to attain the long-term goal, it's harder to evaluate complex initiatives and less likely that all key factors are addressed. Positive monitoring practices can be seen as inputs in the theory of change, and their effects can be seen as contributing to the intended outcome. As part of the project planning, monitoring, and monitoring cycle, the Change Theory is integrated or utilized at various times. Included in the scope and strategic analysis are the stages of conceptualization as well as planning.


1.3.2. Theory of Constraints

In 1984, Eliyahu Goldratt introduced the theory of limitations. This management philosophy focuses on three levels of change: organization thinking, organization measures and organization procedures. One of the fundamental assumptions in this theory is that the organization may be judged by assessing the operational expenses and overall investment in it.

To venture managers, three restrictions are essential to a venture's success. Achieving an auspicious conclusion by streamlining these three elements will teach you how to extend quality. There are individual impacts on venture execution from task scope (a measure of worth), cost, and time; nonetheless, because these components have some interaction, one vital has an impact on the other two, affecting venture expectancies to a greater extent Hamid, Ahmad, Shah & Arshad 4.


1.3.3. Complexity Theory

Complexity theorist Stuart Kauffman opines that we are living in a world of complexity and change. Studying nature from a socio-authoritarian point of view, and how these effects might be used to create a more efficient framework for business transportation. It should, in particular, allow executives to react to core activities and improve tasks, the style of administration received, and the process of fundamental leadership, among other things. Administratively, this notion regarding unpredictability opens up an entirely new world of possibilities, especially in the fields of administration and venture capitalist management.

Complexity management is possible if the characteristics are identified and a framework has been built with the help of project managers.

2. Research Methodology

The research design was descriptive cross sectional and correlational. The study adopted a mixed mode research approach in which quantitative and qualitative research methods were applied concurrently. Using this design, the study was able to describe or explain the link that existing between variables without affecting those associations. The descriptive research method speeded up the acquisition of data. It allowed for the collection of accurate as well as high-quality research data. The target population for this study was 1100, which comprised County Chief Officers, County Engineers, Sub County Administrators, Ward Administrators, Departmental directors, Project Inspectors, Project implementation committee members, and Community members. Further breakdown is indicated in Table 1.

According to Kothari & Garg, sample is the number of items to be selected from the universe for examination while sampling procedures are the techniques used to select the samples from a population. These are outlined below;

The study used the Krejcie and Morgan table for sample size determination. The entire population for the study is 1100. From the Krejcie and Morgan tables (1970) the sample size is 285 at 95% level. The resulting sample size for the different strata of target population is shown in Table 2.

Both probability and non-probability sampling techniques were employed in this study. Simple random sampling was used under probability sampling technique whereas, purposive sampling was used under non probability sampling technique. Research instruments included self-administering questionnaires.

The research instruments were taken through pilot testing for validity and reliability. The piloting took place in Bondo Sub County, Siaya County a neighbor to Kisumu east Sub County. Bondo Sub County, runs a similar devolved road construction project. The pilot study was undertaken on a convenience sample of 10 M&E staff members who did not form part of the sample that was used in the study representing 10% minimum sample size sufficient to establish internal validity and consistence of the research instruments This was done at least two weeks before the actual data collection period. Piloting helped to counter check wording of questions, such that respondents would be able to give the desired response as per the questions and to determine the time it would take to fill in each questionnaire. The pre-test method was used to determine the stability and reliability of the instruments over the time and re-test method was carried out on the corrected questionnaire to determine if the questionnaire achieved the recommended threshold of α= 0.70 before the instrument is deemed fit for use in the study.

In this study, Content validity was used. This was established through expert consultations with peers, study supervisors and M&E experts. To establish content validity, two specialists in the area of study who are the research supervisors from the University of Nairobi were given the instruments to examine the instrument's items relevance and consistence to the objectives by rating each item on a scale of very relevant (4), relevant (3), somewhat relevant (2), and not relevant (1). Content Validity Index (CVI) was used to determine validity

CVI= Items rated 3 or 4 by both experts divided by the total number of items in the questionnaires. The results summarized in Table 3 were obtained.

Table 3 shows that validity index: CVI= = 0.80, which is acceptable since it was more than the threshold of 0.7 recommended by Cohen and Swerdlik. Hence out of any ten items used in this study, at least seven of them measured what they were intended to measure.

Reliability of the research instruments represents their ability to turn out same results if repeatedly applied on the same target population. The reliability of the instrument in this study was confirmed through pilot study. Pre-test of reliability method was used to determine the stability and reliability of the instruments over the time and re-test of reliability method was carried out on the corrected questionnaire to determine if the questionnaire achieved the recommended threshold of α= 0.70 before the instrument could be deemed fit for use in the study (Cronbach and Azuma, 1962). The study employed Cronbach’s Alpha coefficient test reliability of the rating scaled questionnaire and items deleted in order to maximize their reliability coefficient. The coefficient was then compared against a threshold of α= 0.70 as a coefficient test for reliability as suggested by Cohen and Swerdlick

The researcher employed Test re-test method by issuing the questionnaire to the 29 piloted respondents in Bondo Sub County M&E officers piloted respondents on two occasions. After one week, the instruments were re-tested with the same group from Bondo Sub County; in this case, respondents were issued with the questionnaires that had been fine-tuned to ensure there was uniformity in responses as compared to earlier questionnaire. The re-test feedbacks were found to be the similar and the instruments were readily used for the actual study. As Creswell (1994) indicates a reliable research instrument should have a composite Cronbach Alpha Reliability Coefficient of at least 0.7 for all items under study and where Alpha < 0.7, then the research instruments were revised before field work to acceptable level. In the pilot test (Test Re-Test). The piloted sample generated a Cronbach alpha of 0.80 This Coefficients were considered reliable enough for this study.

The investigator requested Kisumu East Sub-County construction project management committee members for their permission and contact information. Community members and stakeholder groups were contacted by the investigator for their preferred manner of administering the questionnaire, whether it be via email or drop off and pick up. The Researcher sought authority from national Commission for science and Technology (NACOSTI) and when it was issued the researcher notified the county Commissioner and county government about the intention to carry out the research. When it came to administering surveys, some were sent to respondents by email, while the remainder were done using drop-and-pick method. Within one week, the surveys gathered from the respondents were then analyzed.

All questionnaires were numbered and the data was coded after data collection. During preliminary editing, the raw data was rigorously reviewed, validated, and cleaned for completeness, consistency, and comprehensibility. Unanswered questions and contradictions were eliminated. As a data analysis tool, SPSS version 20 (Statistical Package for Social Sciences) was used for data analysis and processing.

In this research study, descriptive and inferential statistics were the key forms of analysis. Descriptive statistics showed where the most of the data set fall and the extent to which the data extend from the center. Tools that were employed for descriptive statistics were frequency counts, percentages, mean, standard deviation, composite mean and composite standard deviations. Determination of the relationship between variables was done using Pearson correlation. The coefficient of the Pearson correlation showed the strength and direction of the association of the beneficiary monitoring and implementation of county government devolved road construction projects in Kisumu east sub county, Kisumu county.

The correlation of determination was employed to analyze how differences in beneficiary monitoring is explained by the implementation of devolved roads projects. The correlation of determination gives a percentage or proportion in the dependent variable that is explained by the independent variable. The regression model developed was tested using the ANOVA test to determine the influence of the beneficiary monitoring on implementation of county government devolved roads. Using the Pearson correlation p-values under 2-tailed, the following five hypothesis were tested:

Model for Hypothesis; There is no statistically significant relationship between Beneficiary needs assessment and implementation of devolved road construction projects in Kisumu east sub county, Kisumu county, Kenya.

Implementation of devolved road construction projects = ƒ (Beneficiary needs assessment, random error)

Where β0- Population’s regression constant, X2 – Beneficiary needs assessment, βi the regression coefficient of Beneficiary needs assessment and ε -is the Model error variable

The multiple regression model was based on the following assumptions which were subjected to statistical diagnosis;

Normality assumptions, Linearity assumption, Multicollinearity and Auto-correlation assumptions.

To arrive at empirical conclusions tests of various hypotheses were conducted at α=0.05 significance level. For P<0.05, H0 was rejected and HA accepted. Table 4 indicate the summary of the research hypothesis, decision rule and the interpretation of the expected results.

3. Results

3.1. Questionnaire Return Rate

Out of the sample size of 285 from the target population who were issued with questionnaires, 285 dully filled and returned the questionnaires giving a return rate of 100%. Table 5 shows the Questionnaire Return Rate from the respondents.

The high return rate was attained because the researcher consistently followed up all the sampled respondents by maintaining physical contacts and constant phone calls. The high return rate of 100% facilitated gathering of sufficient data that could be generalized to determine the influence of Beneficiary Monitoring on Implementation of Devolved Road Construction Projects in Kisumu East Sub County, Kisumu County. data that could be generalized to represent the opinions of participants.

3.2. Demographic Characteristics of the Respondents

In order to understand the characteristics of participants the researcher was dealing with in the study, their background information was necessary. The study sought information from the participants on distribution by, gender, age, educational level and position category in County Government. The participants were asked to provide this demographic information. The results are presented in Table 6 and are further discussed in the following subsequent sub themes.


3.2.1. Distribution of Respondents by Gender

It was imperative to investigate the respondents’ gender to establish gender parity in Beneficiary Monitoring and Implementation of County Government Devolved Road Construction Projects in Kisumu East Sub County, Kisumu County. The information sought on gender was significance to the Kisumu County Government for policy decisions on Implementation of County Government Devolved Road Construction Projects. Table 6 shows that over 50% of the respondents at 175(61.4%) were males while their female counterparts were 110(38.6%). The findings indicated that Male study participants outnumbered their female counterparts, implying that there was still gender parity. The implication of this result to the study is that majority of men devote their time and get preoccupied in beneficiary Monitoring and Implementation of County Government Devolved Road Construction Projects in Kisumu East Sub County as compared to the female counterparts.


3.2.2. Distribution of the Respondents by Age

Research participants were also asked to provide their age to ascertain whether they were distributed normally in terms of age group. Age representation across the age brackets were used to ensure that the results represent views across all the age groups. Table 6, indicates that 29 (10.2%) were between 18- 20 years, 50 (17.5%) were in the 21-25 years’ category, 52 (18.2%) were aged between 26-30 years, 46 (16.1%) were aged between 31-35 years, 48 (16.8%) were aged between 36-40 years, 44 (15.4%) were aged between 41-45 years while 16 (5.8%) were above 45 years of age. This distribution is skewed to older age groups as evidenced by 72.3% of the respondents who were aged 26 years and above; implying that most of the respondents were mature persons, therefore, expected to respond adequately to the questions relating to beneficiary Monitoring and Implementation of County Government Devolved Road Construction Projects in Kisumu East Sub County.


3.2.3. Distribution of Respondent by Level of Education

The respondents were also asked to indicate their level of education. The level of Education of the respondent was significant in providing knowledge for understanding the influence of beneficiary monitoring on Implementation of County Government Devolved Road Construction Projects in Kisumu East Sub County, Kenya. The study findings indicated that 29 (10.1%) had primary certificate qualification, 70 (24.6%) had secondary certificate qualification, 55 (19.3%) had certificate qualification, 77 (27%), had diploma qualification, 44(15.4%) had bachelor’s degree qualification, 7(2.5%) had master’s degree qualification and 3 (1.1%) had other educational qualification. The implication of this findings to the study is that 65.3% of the respondents were educated beyond secondary school, hence, expected to understand and objectively respond to the questions put to them regarding beneficiary Monitoring and Implementation of County Government Devolved Road Construction Projects in Kisumu East Sub County.


3.2.4. Distribution of Respondents by Position Category in the County Government

It was imperative to investigate the respondents’ position category to establish how beneficiary Monitoring and Implementation of Devolved Road Construction Projects in Kisumu East Sub County were related with cadre of the educational background; whose information were considered to be significance to the road construction agencies for policy decision making.

Table 6, shows that 1(0.4%) was categorized as county chief officer, 4(1.4%) each were categorized as sub county administrator, departmental director and project inspectors respectively, 3(1.1%) were categorized as county engineers structural, 5(1.6%) were categorized as ward administrators, 245(86%) were categorized as community members and 19 (6.7%) were categorized as project implementation committee members. The findings on position category indicates that beneficiary Monitoring and Implementation of Devolved Road Construction Projects in Kisumu East Sub County are undertaken by qualified personnel capable of responding to information sought on beneficiary Monitoring and Implementation of County Government Devolved Road Construction Projects in Kisumu East Sub County.

4. Beneficiary Needs Assessment and Implementation of Devolved Road Construction Projects

Beneficiary Needs Assessment in this study is defined as the identification of the various reasons a particular project should be undertaken in a particular area. The participants were requested to give their opinions on their level of agreements or disagreements with the five statements of Beneficiary Needs Assessment on a Likert scale of 1-5 where Strongly agree(SA)=5, Agree(A)=4 Neutral(N)=3, Disagree(D)=2and Strongly disagree. (SD)=1. The results were analyzed and presented using frequencies, percentage, means and standard deviation for each response in each item. The item mean as well as the standard deviation were also computed and presented alongside as provided in Table 8.

The results in Table 8 indicates that the composite mean and composite Standard deviation for Beneficiary needs assessment were 4.30 and 0.910 respectively; implying that using the Likert scale a majority of participants agreed (mean=4.30) that Beneficiary needs assessment influence Implementation of Devolved Road Construction Projects. Similarly, five statements were developed to measure the extent of influence of Beneficiary needs assessment on Implementation of Devolved Road Construction Projects.

Statement (1) that ‘Implementation of county devolved road construction projects enhances accessibility of the area by the locals’ had a mean of 4.16 and a standard deviation of 0.692. This results indicate that out of 285 study participants, 175(61.4%) strongly agreed, 108 (37.9%) agreed, 1(0.4%) were neutral, 1(0.4%) disagreed and 0(0.00%) strongly disagreed that Implementation of county devolved road construction projects enhances accessibility of the area by the locals. This results shows that the line statement mean score of 4.16 was lower than the composite mean of 4.30; The implication of this result to the study is that Implementation of county devolved road construction projects has not been adequately done in order to enhance accessibility of the area by the locals and hence negatively influence of Implementation of Devolved Road Construction Projects. The lower line item standard deviation of 0.692 than the composite standard deviation of 0.910 indicate that there was a convergence opinion among the study participants. The study results supports finding by Musyoka, AN 5 in his research who found out that adequate Implementation of county devolved road construction projects enhances accessibility of the area by the locals.

Statement (2) that ‘Implementation of county devolved road construction projects leads to reduction in criminal activities’ had a mean of 4.17 and a standard deviation of 0.704. This results indicate that out of 285 study participants, 91(31.9%) strongly agreed, 145(50.9%) agreed, 29(10.2%) were neutral, 15(5.3%) disagreed and 5(1.8%) strongly disagreed that Implementation of county devolved road construction projects leads to reduction in criminal activities. This results shows that the line statement mean score of 4.17 was lower than the composite mean of 4.30; The implication of this result to the study is that Implementation of county devolved road construction projects has not been done enough reduce criminal activities and hence negatively influence of Implementation of Devolved Road Construction Projects. The lower line item standard deviation of 0.704 than the composite standard deviation of 0.910 indicate that there was a convergence opinion among the study participants. The study results supports finding by Musyoka, A.N 5 in his research who found out that adequate Implementation of county devolved road construction projects leads to reduction in criminal activities.

Statement (3) that ‘Implementation of county devolved road construction projects leads to creation of business opportunities’ had a mean of 4.29 and a standard deviation of 0.657. This results indicate that out of 285 study participants, 79(27.7%) strongly agreed, 163(57.2%) agreed, 13(4.6%) were neutral, 20(7%) disagreed and 10(3.5%) strongly disagreed that Implementation of county devolved road construction projects leads to reduction in criminal activities. This results shows that the line statement mean score of 4.29 was slightly lower than the composite mean of 4.30; The implication of this result to the study is that Implementation of county devolved road construction projects leads to creation of business opportunities and hence moderately influence of Implementation of Devolved Road Construction Projects. The lower line item standard deviation of 0.657 than the composite standard deviation of 0.910 indicate that there was a convergence opinion among the study participants. The study results supports finding by Musyoka, A.N 5 in their research who found out that Implementation of county devolved road construction projects leads to creation of business opportunities.

Statement (4) that ‘Implementation of county devolved road construction projects leads to establishment of hospitals’ had a mean of 4.34 and a standard deviation of 0.650. This results indicate that out of 285 study participants, 99(34.7%) strongly agreed, 126(44.2%) agreed, 33(11.6%) were neutral, 18(6.3%) disagreed and 9(3.2%) strongly disagreed that Implementation of county devolved road construction projects leads to establishment of hospitals. This results shows that the line statement mean score of 4.34 was higher than the composite mean of 4.30; The implication of this result to the study is that Implementation of county devolved road construction projects leads to establishment of hospitals and hence positively influence of Implementation of County Government Devolved Road Construction Projects. The lower line item standard deviation of 0.650 than the composite standard deviation of 0.910 indicate that there was a convergence opinion among the study participants. The study results supports finding by Musyoka, A.N 5 in his research who found out that Implementation of county devolved road construction projects leads to establishment of hospitals.

Statement (5) that ‘Implementation of county devolved road construction projects leads to emergence of market centers. had a mean of 4.34 and a standard deviation of 0.614. This results indicate that out of 285 study participants, 64(22.5%) strongly agreed, 175(61.4%) agreed, 16(5.6%) were neutral, 18(6.3%) disagreed and 12(4.2%) strongly disagreed that Implementation of county devolved road construction projects leads to emergence of market centers. This results shows that the line statement mean score of 4.34 was higher than the composite mean of 4.30; The implication of this result to the study is that Implementation of county devolved road construction projects leads to emergence of market centers and hence positively influence of Implementation of County Government Devolved Road Construction Projects. The lower line item standard deviation of 0.614 than the composite standard deviation of 0.910 indicate that there was a convergence opinion among the study participants. The study results supports finding by Muriithi et. all 6 in their research who found out that Implementation of county devolved road construction projects leads to emergence of market centers.

These findings were also corroborated by the key informants during the interview session who had this to say in line with beneficiary needs assessment and Implementation of County Government Devolved Road Construction Projects

Due to Implementation of County Government Devolved Road Construction Projects we do have newly developed market centers, schools and emerging business opportunities to the community. (Respondent 7).

4.1. Correlation Analysis of Beneficiary Needs Assessment and Implementation of Devolved Road Construction Projects

The study sought to examine the relationship between Beneficiary needs assessment and Implementation of County Government Devolved Road Construction Projects. Pearson correlation coefficient was used to test the relationship between Beneficiary needs assessment and Implementation of Devolved Road Construction Projects at 95% level of confidence. The correlations results obtained are shown in Table 9.

In order to determine the correlation between Beneficiaries needs assessment and Implementation of Devolved Road Construction Projects, Pearson correlation coefficient was run on the scores of each scale. The total scores of the scales were computed as a summation of the individual scores on each item by the respondent at 95% level of confidence. The study found a positive overall correlation(r=0.296) which was statistically significant as P-value 0.000<0.05(p=0.000). This implies that there is a significant relationship between Beneficiaries needs assessment and Implementation of Devolved Road Construction Projects leading to rejection of the null hypothesis (H0: There is no significant relationship Beneficiaries needs assessment and Implementation of Devolved Road Construction Projects) and acceptance of the alternative hypothesis, and hence the research findings conclude that there is a significant relationship between Beneficiaries needs assessment and Implementation of Devolved Road Construction Projects. This finding is in agreement with findings by Muriithi et. all 6 found that there is a significant relationship between Beneficiaries needs assessment and Implementation of County Government Devolved Road Construction Projects.

4.2. Regression Analysis of Beneficiaries Needs Assessment on Implementation of Devolved Road Construction Projects

Simple linear regression was adopted to investigate how Beneficiaries needs assessment influence Implementation of Devolved Road Construction Projects. The rational of using the simple regression model was to establish how Beneficiaries needs assessment as a predictor significantly or insignificantly predicted Implementation of Devolved Road Construction Projects.


4.2.1. Model summary of Beneficiaries Needs Assessment on Implementation of Devolved Road Construction Projects

The model summary sought to determine how Beneficiaries needs assessment is a predictor that significantly or insignificantly predicted Implementation of Devolved Road Construction Projects. The regression model summary results are presented in Table 10.

The model summary Table 10 suggest that there is a positive correlation (R=0.296) between Beneficiaries needs assessment on Implementation of Devolved Road Construction Projects and those predicted by the regression model. In addition, 8.8% of the variation in the Implementation of County Government Devolved Road Construction Projects is explained by Beneficiaries needs assessment. The results are consistent with the findings of a study by Muriithi et. all 6 who found out variation in the Implementation of County Government Devolved Road Construction Projects is explained by Beneficiaries needs assessment


4.2.2. ANOVA of Beneficiaries Needs Assessment on Implementation of Devolved Road Construction Projects

The study sought to establish if the regression model is best fit for predicting construction cost overruns in real estate projects after use of Beneficiaries needs assessment. The ANOVA results are presented in Table 11.

The ANOVA results from Table 10 indicated that (F-statistics (1,283) =27.252 is significant since the P-value 0.000< 0.05 implying that the predictor co-efficient is at least not equal to zero. and hence the regression model results in significantly better prediction of Implementation of County Government Devolved Road Construction Projects. The results are consistent with the findings of a study by Muriithi et. all 6 who found out that Beneficiaries needs assessment significantly predict better Implementation of Devolved Road Construction Projects.


4.2.3. Coefficients for regression of Beneficiaries Needs Assessment and Implementation of Devolved Road Construction Projects

The study sought to establish whether there was influence of Beneficiaries needs assessment on Implementation of Devolved Road Construction Projects. The regression coefficients results are presented in Table 12.

5. Summary of findings

The research objective was to examine the extent to which Beneficiaries needs assessment influence implementation of Devolved Road Construction Projects. The composite mean and composite Standard deviation for Beneficiaries needs assessment were 4.30 and 0.910 respectively; implying that using the Likert scale, the respondents agreed that Beneficiaries needs assessment influence implementation of Devolved Road Construction Projects. The overall correlation coefficient for Beneficiaries needs assessment and implementation of Devolved Road Construction Projects was found to be 0.296 with a p-value of 0.000 < 0.05 implying that from the views of participants in the study the results indicated that there was a significant relationship between Beneficiaries needs assessment and implementation of Devolved Road Construction Projects; leading to rejection of the null hypothesis (H0: There is no significant relationship between Beneficiaries needs assessment and implementation of County Government Devolved Road Construction Projects) and acceptance of the alternative hypothesis. The ANOVA results from the study participant’s views indicated that the regression model for Beneficiaries needs assessment results was significantly better prediction of implementation of Devolved Road Construction Projects (1,283) =27.252 and p-value =0.000<0.05). The simple linear regression coefficients result indicated that the test of β2=0.257 (coefficient of Beneficiaries needs assessment) statistics revealed that there was sufficient evidence that Beneficiaries needs assessment was linearly related implementation of Devolved Road Construction Projects (Value of test statistics: t=15.230; p-value =0.000<0.05).

6. Conclusions

The simple linear regression coefficients as well as the Pearson correlation results indicated that there was significant influence of Beneficiaries needs assessment on implementation of Devolved Road Construction Projects. The p-values less than the set threshold of significance; implied that there was a significant influence of Beneficiaries needs assessment on implementation of Devolved Road Construction Projects.

7. Contribution of the Study to the Body of Knowledge

The study filled in the gaps in knowledge in beneficiary needs assessment due to the positive influence of beneficiary needs assessment adequately carried out in this study which ensure enhancement of implementation of devolved road construction projects.

8. Recommendation

8.1. It is recommended that Kisumu East Sub County monitoring officers develops and implements a beneficiary monitoring and visibility plan for enhancing sustainable implementation of devolved road construction projects in Kisumu East Sub County, Kisumu County.

8.2. It is recommended that Kisumu East Sub County monitoring officers conducts beneficiary needs assessment prior to implementation of devolved road construction projects in Kisumu East Sub County, Kisumu County.

8.3. It is recommended that Kisumu East Sub County monitoring officers involve all stakeholders in their planning and monitoring of implementation of devolved road construction projects in Kisumu East Sub County, Kisumu County.

References

[1]  Hoogeveen, J. and Taptué, A.-M. (20), Iterative Beneficiary Monitoring of Donor Projects, World Bank, Washington, DC, USA.
In article      
 
[2]  IFRC, Project/Programme Monitoring and Evaluation Guide, The International Federation of Red Cross
In article      
 
[3]  McLellan A., DOES THE DISTRIBUTION OF READY TO USE FOOD PRODUCTS FOR THE PREVENTION OF UNDERNUTRITION MEET THE ULTIMATE NEEDS OF THE BENEFICIARY? African Journal of Food, Agriculture, Nutrition and Development (14):3.
In article      
 
[4]  Ab Hamid, N. R., Ahmad, F., Shah, S. N. T., & Arshad, N. H. E-SERVICE QUALITY AS A BUILDING BLOCK TO LONG-TERM CUSTOMER RELATIONSHIPS-A CUSTOMER PREFERENCE MODEL. International Journal of Arts & Sciences, 5, 285.
In article      
 
[5]  Musyoki, A. N. Institutional Factors Influencing Implementation of Infrastructure Projects by County Governments In Kenya; A Case Of Embu County, Kenya (Doctoral dissertation, University of Nairobi).
In article      
 
[6]  Muriithi, Caroline Wachuka, and Mary Nyawira Mwenda. “Technology and quality of road construction projects in Kenya: a focus on contractor’s exposure to technology in Machakos Sub-County.”
In article      
 

Published with license by Science and Education Publishing, Copyright © 2022 Sule George Aggrey Ochieng and Abuya Isaac Odhiambo

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Cite this article:

Normal Style
Sule George Aggrey Ochieng, Abuya Isaac Odhiambo. Beneficiary Needs Assessment on Implementation of Devolved Road Construction Projects in Kisumu East Sub-County, Kisumu County, Kenya. Journal of Business and Management Sciences. Vol. 10, No. 1, 2022, pp 20-29. http://pubs.sciepub.com/jbms/10/1/3
MLA Style
Ochieng, Sule George Aggrey, and Abuya Isaac Odhiambo. "Beneficiary Needs Assessment on Implementation of Devolved Road Construction Projects in Kisumu East Sub-County, Kisumu County, Kenya." Journal of Business and Management Sciences 10.1 (2022): 20-29.
APA Style
Ochieng, S. G. A. , & Odhiambo, A. I. (2022). Beneficiary Needs Assessment on Implementation of Devolved Road Construction Projects in Kisumu East Sub-County, Kisumu County, Kenya. Journal of Business and Management Sciences, 10(1), 20-29.
Chicago Style
Ochieng, Sule George Aggrey, and Abuya Isaac Odhiambo. "Beneficiary Needs Assessment on Implementation of Devolved Road Construction Projects in Kisumu East Sub-County, Kisumu County, Kenya." Journal of Business and Management Sciences 10, no. 1 (2022): 20-29.
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  • Table 9. Correlation analysis of Beneficiary needs assessment and Implementation of Devolved Road Construction Projects (n=285); *Correlation is significant at 0.05 level (2-tailed)
  • Table 10. Regression Model Summary table of Beneficiaries needs assessment on Implementation of Devolved Road Construction Projects
  • Table 11. An ANOVA of the Regression of Beneficiaries needs assessment on Implementation of Devolved Road Construction Projects
  • Table 12. Coefficients for the Regression of Beneficiaries needs assessment and Implementation of Devolved Road Construction Projects
[1]  Hoogeveen, J. and Taptué, A.-M. (20), Iterative Beneficiary Monitoring of Donor Projects, World Bank, Washington, DC, USA.
In article      
 
[2]  IFRC, Project/Programme Monitoring and Evaluation Guide, The International Federation of Red Cross
In article      
 
[3]  McLellan A., DOES THE DISTRIBUTION OF READY TO USE FOOD PRODUCTS FOR THE PREVENTION OF UNDERNUTRITION MEET THE ULTIMATE NEEDS OF THE BENEFICIARY? African Journal of Food, Agriculture, Nutrition and Development (14):3.
In article      
 
[4]  Ab Hamid, N. R., Ahmad, F., Shah, S. N. T., & Arshad, N. H. E-SERVICE QUALITY AS A BUILDING BLOCK TO LONG-TERM CUSTOMER RELATIONSHIPS-A CUSTOMER PREFERENCE MODEL. International Journal of Arts & Sciences, 5, 285.
In article      
 
[5]  Musyoki, A. N. Institutional Factors Influencing Implementation of Infrastructure Projects by County Governments In Kenya; A Case Of Embu County, Kenya (Doctoral dissertation, University of Nairobi).
In article      
 
[6]  Muriithi, Caroline Wachuka, and Mary Nyawira Mwenda. “Technology and quality of road construction projects in Kenya: a focus on contractor’s exposure to technology in Machakos Sub-County.”
In article