The Effect of Tendering Strategy on Service Delivery of Water Flagship Projects in Kenya

Tendering is a subset of procurement (broadspectrum) that involves the critical step of inviting and evaluating bids from potential contractors to carry out specific parts of the project. Together, these processes dictate the operational efficiency and economic feasibility of construction projects and ensure adherence to quality, legal standards, and fair-trade practices. As we explore these pivotal components of construction project management, we uncover the strategies, challenges, and best practices that guide successful project outcomes in an ever-evolving construction landscape. The Kenyan government has consistently raised funding for hygiene and water flagship programes. In the 2013–2014 financial year, for example, the overall growth spending on water supply and related services increased from KShs. 20.5 billion in 2012–2013 to KShs. 44.5 billion. This study concentrates on the influence of tendering on service delivery at a strategic level instead of routines, procedures, and practices, or the overall procurement strategy. Thus, this research respond to the following research question: What is the impact of the tendering strategy on the service delivery of water flagship projects in Kenya? The specific objective of this study is to establish the effects of a tendering strategy on the delivery service of water flagship projects in Kenya. The results show that the effects of tendering strategy on the service delivery of water flagship projects in Kenya are statistically significant. The results of the variable-level analysis indicate that 75.0% of the total tendering approach explains differences in service delivery, while the results of the indicator-level analysis indicate that 56.7% of the total variations in service delivery are explained by four indicators of tendering strategy: negotiated tendering, two-stage tendering-, and -single-stage competitive tendering. This study empirically tested the link between tendering strategy and service delivery outside the challenges documented by study on the domestic governance structure and urban service delivery in Zimbabwe and found that their relationship is statistically significant. This study makes an important contribution to the literature for policymakers. The Kenya National Water Policy elaborates on the development of various policies, regulatory and legislative frameworks to guide the water sector in Kenya. This advanced the concept of tendering strategy and service delivery as studied on this paper. 

Introduction

Background of the Study

Tendering is essential for service delivery worldwide, and has a significant impact on the performance of government departments’. It performs the fiduciary duty to ensure efficiency in the acquisition of goods, works, and services to the public. The process of tendering in the public sector occurs under the regulations and laws of procurement, and this varies from country to country. The government is responsible for ensuring that the utilization of resources is conducted in a very efficient, ethical, and transparent manner to promote sustainable development and improvement the standards of service provision and the economy (Van den Abbeele & Warlop, 2006; Uyarra & Flanagan, 2010; Ahmedet al., 2014).

According to the Construction Placement Journal (2024), tendering is a subset of procurement (broad-spectrum) that involves the critical step of inviting and evaluating bids from potential contractors to carry out specific parts of the project. Together, these processes not only dictate the operational efficiency and economic feasibility of construction projects, but also ensure adherence to quality, legal standards, and fair-trade practices. As we explore these pivotal components of construction project management, we uncover the strategies, challenges, and best practices that guide successful project outcomes in an ever-evolving construction landscape. By guaranteeing that the greatest deal is made for each particular good or service, the company aims to save expenses and boost productivity. A specific price range makes it clear to prospective bidders what they must offer to be considered. By guaranteeing that only eligible contractors are considered, waste and corruption are reduced.

According to the Oboloo team 2023, a tender is a call for offers, frequently from a public entity or government, to acquire goods or services. The lowest price that the requester is willing to pay for an item or service may be specified as tender. The top bidders are frequently chosen based on pricing and other relevant considerations. Tenders may also promote competitiveness by leveling the playing field for interested parties. Bidders are more likely to focus on fulfilling the tender’s conditions rather than competing with one another if the number of submissions is restricted. By guaranteeing that the best bid is made for any particular good or service, the tender serves to save expenses and boost productivity. A specific price range makes it clear to prospective bidders what they must offer to be considered. By guaranteeing that only eligible contractors are considered, -waste and corruption are reduced. Tenders may also promote competitiveness by leveling the playing field for interested parties. Bidders are more likely to focus on fulfilling tender’s conditions rather than competing with one another if the number of submissions is restricted.

Service delivery is—an endless loop-like procedure for developing and providing customer-oriented products and services promptly and in a timely manner. Economic globalization and refined and segmented customers have triggered the need for customized service delivery processes. This has led organizations to seek ways to handle new businesses and opportunities to suit customers who are evolving towards service customization, price, uniqueness, and quality. This trend has made firms utilize their capabilities, such as applying new technologies, and skills, and the design, development, and implementation of service delivery processes (Chen & Tsou, 2012; Stark, 2011).

Costa (2011), found that service delivery has four key elements: customer satisfaction index,; customer complaint resolution,; service quality, and service availability. The customer satisfaction index aimed at assessing customer satisfaction with the company’s performance. We assume that a satisfied customer is more likely to remain. The complaint-resolution process that customers embark on is a procedure that allows companies to log, assess, and resolve problems and dissatisfaction (Bill & David, 2011). This study was guided by Institutional Theory.

Kenya is a water-stressed country, and the Kenyan government has continually invested a lot of public resources in water projects to provide much-needed services (Vision 2030). There is less confidence in the general public in public tendering systems because of the news of rampant misappropriation of resources through outright corruption and pilferage, incomplete projects, shoddy projects, lack of adequate stakeholder involvement, and, hence, provision of lip services.

Research Problem

Tendering processes have been a key area of focus for most governments to improve service delivery through proper stakeholder involvement and eradicate the misappropriation of public funds through corruption, delays in project implementation, inadequate supervision and monitoring of projects, inadequate budgeting, and poor project designs,. The strategy is set out before the tendering process and assures the contracting organization that the selected approach is appropriate for the proposed acquisition (Vellapi, 2010; Weishaar, 2013; Johnson & Flynn, 2015).

The Kenyan government has consistently raised funding for hygiene and water flagship programmes. In the 2013–14 financial year, for example, the overall growth spending on water supply and related services increased from KShs. 20.5 billion in 2012–13 to KShs. 44.5 billion (Kenya National Bureau of Statistics, 2014).

The following gaps were identified in this study. Few studies have examined the effect of tendering strategies on service delivery. They focused on tendering procedures and practices but not on strategic-level issues.: For instance, Mbele (2005) assessed tendering procedures, while Samweli (2002) focused on tendering procedures in government organizations. Phillips and Piotrowicz (2006) established a tendering implementations in construction companies. This study concentrates on the influence of tendering on service delivery at a strategic level, as opposed to routines, procedures, and practices, or the overall procurement strategy. Therefore, this study addressed the following research question: How does Kenya’s water flagship projects’ service delivery depend on the tendering strategy?

According to Kariuki (2015), the water sector is essential to the social and economic development of every country. Stakeholders will find value in the study’s findings, which will influence how they contribute to the operationalization of important flagship water projects. This study contributes to procurement theories by examining the effect of tendering strategy on service delivery. This contributes to broadening the available knowledge to the bodies of procurement professionals and practitioners.

Research Objective

The aim of this research is to establish the effect of tendering strategies on the service delivery of water flagship projects in Kenya.

Theoretical and Empirical Literature Review

Institutional theory (Scott, 2005) points out that the institutions entail regulative and cultural-cognitive factors that give life purposes by combining the three institutional pillars of culture, cognition, norms, and regulation with relevant resources and activities. The cultural-cognitive column involves joint comprehension (common symbols, philosophies, and shared understanding). The normative pillar alludes to values (desirable or preferable), norms (how things are supposed to be carried out), and social obligation as a compliance basis. The regulatory column stresses the application of sanctions, laws, and rules as being enforcement approaches with experience as being a compliance basis. Institutional theory has become a key lens for studying every type of organizational phenomenon (Ashworthet al., 2009), in particularly, it is suitable for research on tendering in organizations, since they are thought to be more vulnerable to institutional forces (Frumkin & Gelaskiewicz, 2004). There is a high likelihood that a public sector organization that tenders might be influenced greatly by the experiences and behaviors of their peers, governmental initiatives, and policy. The theory suited the project to the execution of the procurement law, practice, and policy in public institutions.

Chirisa (2010) conducted a study of Zimbabwe’s urban service delivery and domestic governance system. The selected cities were included in the case study. Research papers, reports, minutes, and document reviews of previously published studies were also examined. The study found that the major problems in the delivery of services were poor infrastructural maintenance, incompetent government, lack of clean water, limited accessibility to health-care, poor refuse collection, and lack of inefficiency and funding.

These outcomes align with Mbele’s (2005), that tendering procedures, when followed effectively, bring a good outcome. If there is no adherence to the procedures of tendering, there is a rise in corruption, and the tender could be given to bidders who are not qualified, as illustrated above; consequently, there will be a supply of low-quality services and goods, thus failing to satisfy the set goals. However, the research did not link the effectiveness of the tendering strategy to service delivery; therefore, this study addressed this gap. Most studies in this field have not pointed out how tendering affects service delivery.

The problem could be that this area is not common because only a few studies have been carried out so far, and the available results by researchers are not enough to make a general conclusion. Hence, there is a knowledge gap.

Conceptual Framework and Hypothesis

The argument derived from the reviewed studies led to the formulation and illustrations of the hypothesis (Fig. 1). This study evaluates the impact of Kenya’s water flagship projects on service delivery.

Fig. 1. Conceptual model.

The following hypothesis was developed from the studies:

H_a1: The Tendering strategy has a significant effect on the service delivery of Kenya’s water flagship projects.

Research Methodology

Research Philosophy

Social science scholars have identified different methodologically viewpoints, such as positivism, epistemology,; realism, ontology, axiology, and interpretivism (Gray, 2013). This study was steered by a positivist research philosophy. This approach was used because it allowed for the operationalization of various hypothetical concepts as well as the generalization of the results (Stiles, 2003). This solved a problem under the paradigm of a positivist that followed a series of hypotheses. The reason for this was that the project entailed predefined (a priori) associations that first needed testing of the theory prior to stating that all hypotheses were done with a predictive rigor for acceptance, which focused on arriving conclusions that are positivistic.

Research Design

Since it was the most effective way to determine the combined impact of these study factors, a cross-sectional survey method was used. Using a descriptive design, it is possible to gather data on individuals without changing the research setting (Babbie, 2010). The procedure required no follow-up, maximized the completeness of important data, and had more control over measurements (Mugenda & Mugenda, 2003). Owing to its inferential character, the cross-sectional survey design made it easier to gather information that allowed the hypotheses to be tested to answer the research questions.

Population of the Study and Sampling Technique

Population was used as the total number of participants, supposed or actual individuals, items, or proceedings from which a researcher intended to generalize the outcomes of the research. This study targeted water flagship projects in Kenya. In total, 1804 water flagships projects in Kenya formed the research analysis. This study targeted project committees, project managers, and technical officers.

The Determination of the best sample size guaranteed sufficient power to detect statistical significance. This study adopted a stratified proportionate sampling procedure. From 1804,-the selected target population, was stratified into a proportionate sampling procedure that guaranteed that the samples obtained were comparable in size with each stratum. The sample was determined using the sample determination table by Krejcie and Morgan (1970), which provides a sample size of 317 projects (Table I).

Table I. Population Size and Sampling Technique

Category	Frequency	Sample size (n/N * total sample size)
Dams and pans	759	133
Community water projects	209	37
Rural water supply schemes	203	36
Boreholes	586	103
Sewage schemes	9	2
Construction of dykes, canals, gabions	38	7
Total	1804	317

Data Collection

A combination of primary and secondary data was used in this study. A questionnaire was used to collect primary data. In this study, the primary data comprised responses concerning all the research variables. The questionnaire was based on the objectives of this study. This study had structured and unstructured questions. Secondary data were collected from quarterly reports, medium-term reports on annual reports prepared by respective government entities implementing the projects, and Vision 2030 websites. The research personally administered the questionnaires after obtain authorization from the National Commission for Science Technology and Innovation. A short letter of introduction was given to the respondents before administering the questionnaires to explain the nature and significance of the research to respondents during the pilot and the main study.

Operationalization of the Study Variables

This comprised the development of an operative description that facilitated the measurement of research variables. The study variables, their related nature, dimensions, measurement indicators, empirical study sources, measurement scales, and the parts of the designated variables in the questionnaire are highlighted in Table II.

Table II. Operationalization of the Study Variables

Variable	Dimensions	Indicators	Source	Measurement
Tendering strategy	Single-stage tendering strategy	Procurement Planning	Lysons and Farrington (2006), Bajariet al. (2006), Corts and Singh (2004), McMillan and Tadelis (2006)	Likert scale
	Two-stage tendering strategy	Improved specifications and design
	Negotiated tendering strategy	Value for money and timely implementation
	Serial tendering strategy	Reduced procurement process
Service delivery	Customer satisfaction index	Customer satisfaction rates	Figgeet al. (2002), Hubbard (2009), Costa (2011), Bill and David, (2011), Lysons and Farrington (2006), Bajariet al. (2006), Corts and Singh (2004), McMillan and Tadelis (2006)	Likert scale
	Customers complain resolution	Timely resolution
	Service quality	Meeting customer expectation
	Service availability	Accessible services		Likert scale

Validity Test of the Study

To establishing the appropriateness of the collected data on the research variables, all the variables went through a validity test to check whether the instrument could assess what was being anticipated. An instrument’s validity refers to the capacity of a particular scale to measure its intended purpose to Mugenda & Mugenda (2010). Two tests of validity were examined: internal construct and face. A pilot survey was conducted to test the instrument’s facial validity. Ten respondents were given respondents were asked to comments on questions that seemed ambiguous or unclear. The questionnaire was modified and administered to six experts (industry experts, university researchers, and scholars in procurement). The feedback of all the experts assisted in removing double-barreled, vague questions and improving the instrument used in research, which will then be incorporated in the research.

Reliability of the Study

The coefficient alpha is used to measure internal consistency in behavioral sciences is coefficient alpha (Drost & Ilic, 2012). This standard draws from Nunnally in 1978, who posits that in the initial research stages on hypothesized measures or predictor tests of a construct, a 0.70 reliability and beyond is adequate. The objects in the instruments of the study and the resultant data were gathered from respondents and underwent a Cronbach’s alpha test of 0.70.

Data Analysis

The data were cleaned, edited, and coded during data analysis. The questionnaires that will be returned will undergo a check to ensure completeness. Data analysis will be performed using a set of inferential data. Pretests were conducted to verify that the main data analysis method, regression, meet its assumptions. Tests for homoscedasticity, multicollinearity, and normality were also performed. The second phase tested the hypotheses created for this study (Table III).

Table III. Summary of Statistical Tests of Hypothesis

Research objective	Hypothesis	Analytical models	Interpretation
To establish the effect of tendering strategy on service delivery of water flagship projects in Kenya.	Ha1: tendering strategy has a significant effect on service delivery of water flagship projects in Kenya.	Simple and Multiple Regression Analysis:Y = α0+ α1X1+ ε;where Y is service delivery; X1 is tendering strategy; 1 is coefficient estimation of the influence of X on Y; α0 is coefficient approximation of the intercept; ε = error term.	• R2 for goodness-of-fit • F-test for overall significance • t-test for individual significance • Marginal changes

Data Analysis, Findings and Interpretations

Response Rate

The study was carried out among 317 out of 1804 Water Flagships projects, which were selected as the target population, stratified into a proportionate sampling procedure that was adopted to guarantee that the samples obtained were comparable with each stratum’s size (Table IV).

Table IV. Response Rate

Total questionnaires distributed	317
Total questionnaires filled and returned	215
Questionnaires removed after sorting (Poorly filled and blank	07
Questionnaires well filled	208
Total response rate for the study	65.62%

Of the 317 projects that were sampled using the sample determination table by Krejcie and Morgan (1970), only 215 questionnaires were returned, of which only 208 were filled, as seven were poorly filled or blank, especially on service delivery and project performance after sorting. The response rate of 65.62% was excellent, which can be attributed to the research.

Validity Test

To establish the appropriateness of the collected data on the research variables, all the variables went through a validity test to check whether the instrument could assess what was being anticipated. An instrument’s validity refers to the capacity of a particular scale to measure its intended purpose to Mugenda and Mugenda (2010). Two tests of validity were performed; internal construct and face. According to the research findings, the sample sufficiently reflected the population, as shown by the Kaiser-Meyer-Olk in measure of sampling Adequacy of 0.766. This further indicates that the dataset is suitable for data analysis.

Table V shows that all commonalities extraction scores were greater than 0.50. The communality scores ranged from 0.805 to 0.840, indicating that all statements in the study were retained. The commonality scores indicated that the items of the measure were closer to 1 (one), and therefore strong enough to explain the variables used in the study.

Table V. Output for Test of Communalities

Communalities	Initial	Extraction
Tendering strategy	1.000	.840
Service delivery	1.000	.805

Test of Linearity

Linearity shows the expected direct relationship between the independent variable(s) and dependent variable (s). A linear relationship exists between the test variables in a scientific study (Creswell, 2013). The Pearson’s correlation matrix was used to test for linearity, and the results are shown in Table VI.

Table VI. Pearson’s Correlation for Linearity

		(1)	(2)
Tendering strategy (1)	Pearson correlation	1
	Sig. (2-tailed)
	N	208
Service delivery (2)	Pearson correlation	0.750**	1
	Sig. (2-tailed)	0.000
	N	208	208

Table VI shows that the correlation matrix results ranged from 0.750 to 1(−p < 0.05). This indicates strong linearity of the variables used in the study.

Hypothesis Testing and Regression Analysis

The findings and outcomes of the regression analysis are recorded and presented in this section. Research objectives, theoretical and empirical literature reviews, and other factors were considered when formulating the hypotheses. Tables VII–XI show the findings of a simple linear regression analysis used to examine the impact of the tendering strategy on the service delivery of waterflagship projects in Kenya.

Table VII. Variables Entered/Removed on the Effect of Tendering Strategy on Service Delivery of Water Flagship Projects in Kenya (Variable Level Analysis)

Variables entered/Removeda
Model	Variables entered	Variables removed	Method
1	Tendering strategya	.	Enter

Table VIII. Model Goodness of Fit on the Effect of Tendering Strategy on Service Delivery of Water Flagship Projects in Kenya (Variable Level Analysis)

Model summary
Model	R	R2	Adjusted R2	Standard error	Change statistics					Durbin-Watson
					R2 Change	F Change	df1	df2	Sig. F change
1	0.750a	0.562	0.560	5.38097	0.562	264.818	1	206	0.000	1.932

Table IX. Model Overall Significance (ANOVAb) on the Effect of Tendering Strategy on Service Delivery of Water Flagship Projects in Kenya (Variable Level Analysis)

ANOVAb
Model		Sum of squares	df	Mean square	F	Sig.
1	Regression	7667.759	1	7667.759	264.818	0.000a
	Residual	5964.686	206	28.955
	Total	13632.445	207

Table X. Regression Coefficients of the Effect of Tendering Strategy on Service Delivery of Water Flagship Projects in Kenya Model coefficients ^a (Variable Level Analysis)

Coefficientsa
	Model	Unstandardized coefficients		Standardized coefficients	t	Sig.
		B	Std. error	Beta
1	(Constant)	.100	2.574		0.039	0.969
	Tendering Strategy	10.448	0.642	0.750	16.273	0.000

Table XI. Variables Entered/Removed on the Effect of Tendering Strategy on Service Delivery of Water Flagship Projects in Kenya (Indicator Level Analysis)

Variables entered/Removeda
Model	Variables entered	Variables removed	Method
1	Single-stage Competitive Tendering Strategy, Negotiated Tendering Strategy, Two-stage Tendering Strategy, Serial Tendering Strategy	.	Enter

Based on the findings in Table VII on the variables entered, the tendering strategy was the only variable that was the most important contributor to the variability and changes in service delivery. According to the research findings in Table VIII, the tendering process has a statistically significant impact on the service delivery of Kenya’s water flagship projects.

The extent to which the tendering process affected the service delivery of Kenya’s water flagship projects was assessed using the goodness-of-fit model shown in Table VIII. The study used simple regression; hence, the interpretation is based on the strength of R-sq (not adjusted R-sq), whereby the higher the R² value, the better the model, and guided by the rule of thumb that R² is always between 0% and 100%.

According to the goodness-of-fit statistics in Table VIII, the model fit the study data well. The R Square value of 0.750 shows that the tendering method accounts for 75.0% of the overall variability in service delivery.

The Regression sum of squares of 7667.759 and model residual of 5964.686, with a mean square of 406.389 for the residual, were obtained from the analysis of variance (ANOVA) of the regression model findings in Table IX. The results of the ANOVA regression showed a p-value of =.000 and F-statistic of 264.818. In addition, the P-value < 0.05 in the coefficient tables and goodness-of-fit statistics demonstrates that the bidding approach has a statistically significant impact on the service delivery of water flagship projects in Kenya, as the P-values of the variables and indicators as well as the overall model are below the significance threshold.

Based on the findings in Table X, the coefficients of the tendering strategy have p-values less than alpha (0.05), meaning that the coefficients for the variable/indicator are all statistically significant. Because the model goodness of fit and coefficients deviate substantially from zero, this study uses the p-values in these variables to reject the null hypothesis.

Consequently, p-values below the significance level of 0.05 are found in the prediction formula for the impact of the tendering method on the service delivery of water flagship projects in Kenya. These findings suggest that the tendering strategy affects service delivery, which is statistically significant, and using the simple linear regression on original (unstandardized) variables produces unstandardized coefficients.; the coefficient for the tendering strategy estimates that service delivery increases by 10.448 units for every single unit intensification in tendering strategy, but the model’s other terms remain constant.

Based on the regression analysis coefficients presented in Table X, the model is expressed as follows.:

$$\begin{array}{r}ServiceDelivery(Y)=f(tenderingstrategy-X)\end{array}$$

$$\begin{array}{r}Y=f\left(X\right)\end{array}$$

$$\begin{array}{r}Y=0.100+0.75X+\epsilon \end{array}$$

Thus, we are unable to reject the hypothesis that the tendering method has a major impact on the service delivery of water flagship projects in Kenya (at a variable level) because it illustrates the importance of tendering strategy in deciding the degree of service delivery.

Multiple linear regression analysis (Indicator Level Analysis) was used to examine the impact of the tendering strategy on the service delivery of water flagship projects in Kenya. The results are presented in Tables XI–XIV.

Table XII. Model Goodness of Fit of on the Effect of Tendering Strategy on Service Delivery of Water Flagship Projects in Kenya (Indicator Level Analysis)

Model Summary
Model	R	R2	Adjusted R2	Standard error	Change statistics					Durbin-Watson
					R2 Change	F Change	df1	df2	Sig. F change
1	0.758a	0.575	0.567	5.34132	0.575	68.708	4	203	0.000	2.026

Table XIII. Model Overall Significance (ANOVAb) on the Effect of Tendering Strategy on Service Delivery of Water Flagship Projects in Kenya (Indicator Level Analysis)

ANOVAb
	Model	Sum of squares	df	Mean Square	F	Sig.
1	Regression	7840.920	4	1960.230	68.708	0.000b
	Residual	5791.525	203	28.530
	Total	13632.445	207

Table XIV. Regression Coefficients of the Effect of Tendering Strategy on Service Delivery of Water Flagship Projects in Kenya Model Coefficients ^a (Indicator Level Analysis)

Coefficientsa
	Model	Unstandardized coefficients		Standardized coefficients	t	Sig.
		B	Std. Error	Beta
1	(Constant)	−0.099	2.598		−0.038	0.970
	Serial tendering strategy	−0.089	1.124	−0.007	−0.079	0.937
	Negotiated tendering strategy	3.479	0.947	0.283	3.673	0.000
	Two-stage tendering strategy	3.997	1.144	0.297	3.493	0.001
	Single-stage competitive tendering strategy	3.139	0.826	0.277	3.800	0.000

Based on Table XI findings on variables entered, the single-stage competitive tendering strategy, negotiated tendering strategy, two-stage tendering strategy, and serial tendering strategy were the only indicators of tendering strategy entered as the most important contributors to the variability and changes in service delivery of water flagship projects.

The strength of the impact of the tendering approach on the service delivery of Kenya’s water flagship projects was assessed using the goodness of fit model in Table XII (Indicator Level Analysis). The study used multiple regression; hence, the interpretation was based on the strength of adj R-sq (not just R-sq), whereby the higher the adj. R² value, the better the model. The adj R-sq was preferred to normal with R-sq, as the model has different numbers of indicators for tendering strategy, and is guided by the rule of thumb that R² is always between 0% and 100%.

According to the findings in Table XII, the tendering approach (at the indicator level) has a statically significant impact on the service delivery of Kenya’s water flagship projects. With an adjusted R Square value of 0.567, the model fits the research data well, according to the goodness-of-fit statistics in Table 5.6. This means that the four indicators of tendering strategy account for 56.7% of the overall variations in service delivery (indicator-level analysis).

A regression sum of squares of 7840.920 and a model residual of 5791.525 with a mean square of 28.530 for the residual were obtained from the analysis of variance (ANOVA) of the regression model findings in Table XIII. A p-value of.000 and F-statistic of 68.708 were obtained from the ANOVA regression findings.

In addition, the p-value < 0.05, in the coefficient tables and goodness-of-fit statistics. The study demonstrates that there is a statistically significant impact of tendering strategy on service delivery, given that the P-values of the overall model and tendering strategy indicators are below the significance threshold (indicator threshold analysis).

From the research data in Table XIV, the only insignificant indicator of the tendering strategy was the serial tendering strategy (p = 0.937). The coefficients of the other three tendering strategy indicators are: negotiated tendering strategy (p = 0.000), two-stage tendering strategy (p = 0.001), and single-stage competitive tendering strategy (p = 0.000),; which have p-values less than alpha (0.05), meaning that the coefficients for the tendering strategy indicators of negotiated tendering strategy, two-stage tendering strategy, and single-stage competitive tendering strategy are all statistically significant. Because the model goodness of fit and coefficients diverge considerably from zero, the study’s use of p-values in these areas cannot rule out the alternative hypothesis.

Therefore, the prediction formula for the effect of tendering strategy indicators (negotiated tendering strategy, two-stage tendering strategy, and single-stage competitive tendering strategy) on service delivery (Indicator Level Analysis) has p-values that are less than the significance level of 0.05. These findings suggested that tendering strategy indicators have a significant effect on service delivery. Whereby,; 0.283 units service delivery was enhanced for each unit of enhanced negotiated tendering strategy,; service delivery is enhanced by 0.297 units for each unit of a well-executed two-stage tendering strategy,; and service delivery is enhanced by 0.277 units for each unit of single-stage competitive tendering intensification.

The model is stated as follows using the regression analysis coefficients shown in Table XIV.:

$$\begin{array}{rl}ServiceDelivery(Y)& =f(TenderingStrategy\\ & -IndicatorLevelAnalysis,X)\end{array}$$

$$\begin{array}{rl}Y& =0.283negotiatedtenderingstrategy\\ & +0.297two-stagetenderingstrategy\\ & +0.277single-stagecompetitivetendering\end{array}$$

$$\begin{array}{r}Y=f(X1-3)\end{array}$$

$$\begin{array}{r}Y=0.283X1+0.297X2+0.277X3\end{array}$$

where X₁ is the negotiated tendering strategy, X₂ the two-stage tendering strategy, and X₃ the single-stage competitive tendering strategy.

Therefore, tendering strategy indicators of negotiated tendering strategy, two-stage tendering strategy, and single-stage competitive tendering strategy are key in influencing service delivery, and we fail to reject the alternate hypothesis that tendering strategy has a substantial impact on the delivery of services for water flagship projects in Kenya (at the indicator level).

Discussion of the Study Findings

Based on the research’s goals and premise, the findings from the testing of the study variables are chronologically presented in this section. The goal of this study was to determine how the service services delivery of Kenya water flagship projects, were impacted by the tendering approach. According to the study’s findings, bidding technique has a statistically significant impact on Kenya water flagship projects’ service delivery. The results at the variable-level analysis indicated that 75.0% of the total differences in the way services are delivered are explained by the tendering strategy. While the results of the indicator-level analysis indicate that 56.7% of the total variations in service delivery are explained by four indicators of tendering strategy: negotiated tendering strategy, two-stage tendering strategy, and single-stage competitive tendering strategy. This study empirically tested the link between tendering strategy and service delivery outside the challenge documented by Chirisa (2010), who conducted research on Zimbabwe’s urban service delivery and domestic governance structure. The study concurs with (Mbele’s, 2005) findings, which indicate that tendering procedures, when followed effectively, bring good outcomes that can service delivery or project performance.

Summary, Conclusions and Recommendations

This section presents the validation of the hypothesis, a summary of the findings, a conclusion, and recommendations for the study findings.

Summary

In the preliminary analysis, the study had a response rate of 65.62%, which is excellent, as it is representative of the study as a unit of analysis. The tendering approach affects the’ service delivery of Kenya water-flagship projects. The results indicate that 75.0% of the total differences in service delivery are explained by the tendering approach (at the variable level), whereas the results at the indicator level analysis indicates that 56.7% of the total variations in service delivery are explained by four tendering strategy indicators: negotiated tendering, two-stage tendering, and single-stage competitive tendering strategies. Therefore, the alternate hypothesis is accepted.

Conclusions

At both the variable and indicator levels, the impact of Kenya’s water flagship project’ bidding method on service performance is statistically significant.

Contributions of the Study Findings

The findings of this study contribute to our understanding of the impact of public tendering, project performance, stakeholder involvement, and service delivery in water flagship and other project implementations in several ways; the study’s findings demonstrated a statistically significant correlation between service delivery and the tendering approach. The current study empirically tested the link between tendering strategy and service delivery outside the challenges documented by Chirisa’s (2010) study, which was conducted over urban service delivery and the domestic government system in Zimbabwe, found that, this relationship is statistically significant.

This study makes an important contribution to the literature for policymakers. The National Water Policy of 2021, which elaborates on the development of various policies and regulatory and legislative frameworks to guide the water sector in Kenya, will benefit the most in advancing the concept of service delivery and stakeholder engagement.

Conflict of Interest

The authors declare that they do not have any conflict of interest.