Tender Awarding Practices and Procurement Performance: A Case of Homa Bay County Government

Keywords: Tender Awarding Practices , Procurement Performance, Price, Promotion of Local Bidders

Paper Type: Research Article

Recommended citation: Akoth, W., & Muturi, W. (2025). Tender awarding practices and procurement performance: A case of Homa Bay County Government. Journal of Economics, Management Sciences and Procurement, 4(1), 261–272.

1.1. Introduction

Tendering is the formal process by which organizations invite offers, bids, or proposals to fulfill specific needs—ranging from the procurement of goods and services to the execution of large-scale projects (Wogube, 2011). Historically, a “tender” could denote any offer of money or service made to settle obligations or secure contracts, with strict legal definitions governed by national statutes and professional bodies (CIPS, 2005). Public entities, in particular, are often bound by procurement regulations that dictate whether contracts must be awarded to the lowest bidder or on value-for-money grounds, and procedures can include open calls via media advertisement, closed bids requiring prequalification, or direct quotation requests (Thomas, 2010). Across these modalities, a rigorous tendering framework aims to promote fairness, accountability, and the best allocation of public and private resources.

With the rise of digital technologies, many large firms have shifted from paper-based to electronic procurement systems, embracing e-bidding, e-tendering, and e-purchasing to streamline workflows. In Argentina, for example, Candela and Ulises (2022) applied contingency theory and technology acceptance theory to show that the adoption of e-sourcing and related practices significantly improved operational and financial performance in Buenos Aires manufacturing firms. A prior study by the same authors (Candela & Ulises, 2020) found that these companies achieved reduced inbound lead times, higher procurement volumes, and stronger profit margins by integrating their e-procurement platforms—a finding echoed by other scholars who emphasize that system interoperability and user training are critical success factors.

Countries around the world have overhauled procurement laws to combat corruption and boost transparency. In Russia, business leaders have adopted simple preventive measures to mitigate corruption risks amid shifting market climates (Business, Corruption, Russia, 2012). France enacted sweeping reforms in the mid-2000s that centralized all tender information on a unified internet portal, minimizing discretionary choice and curbing opportunistic behavior (Yakovlev, Yakobson, & Yudkerich, 2006). In Indonesia, Candra and Gunawan’s analysis highlighted how regulatory clarity, enhanced transparency, and accountability mechanisms can drive economic development by fostering fair competition and reducing procurement malpractices. Similarly, Tunisia’s post-revolutionary government introduced e-procurement in 2011 to extend bid access beyond the capital, thereby reducing travel burdens, information asymmetries, and opportunities for graft (Rahab, 2011).

Within the African context, diverse challenges and innovations have emerged. In Nigeria, Mbachu and Domingo (2014) argued that accurate risk analysis and forecasting of contract prices are vital for protecting profit margins under fixed-price tendering, while Ezekiel (2010) and Onukwube (2002) noted that competitive viability often hinges on contractors’ understanding of project scope, bid pricing strategies, and capacity constraints. Botswana’s approach emphasizes non-fraudulent processes and grants procurement preferences to citizen-owned firms, with defined registration systems and value-based selection criteria (Jodie, 2004; World Bank, 2008). Conversely, Tanzania continues to struggle with lengthy tender evaluations—sometimes exceeding the validity of bids—which has led to project cancellations and wasted budget allocations (World Bank Group, 2023).

Kenya’s procurement framework has evolved from a rudimentary Supplies Manual in 1978 to the comprehensive Public Procurement and Disposal Act of 2005 and its subsequent Regulations (PPOA, 2006; GOK, 2010). Despite these formal structures—and the establishment of oversight bodies such as the Public Procurement Oversight Authority and the Procurement Appeals Board—studies have documented persistent gaps in transparency, record-keeping, and accountability (Kakwezi & Nyeko, 2010). Prior to 2003, poor governance of public assets resulted in severe infrastructure deterioration and widespread poverty (World Bank, 2007; KNBS, 2010). Today, initiatives to integrate departmental procurement plans, enhance ethical compliance through improved compensation for procurement officials, and empower youth participation in counties like Homa Bay aim to bolster integrity and value for money (Basheka, 2008; Mutua, 2010; Ndegwa, 2014).

Despite the suite of legislative reforms designed to enhance efficiency and curb corruption—culminating in the Revised Public Procurement and Disposal Act of 2023—public entities still face challenges of tribalism, political interference, nepotism, and procedural delays that undermine fairness and competitiveness. Recent controversies, such as the decision by Homa Bay County to award a major contract to the highest bidder without donor consultation, have intensified concerns over procurement integrity (Olambo, 2024). Consequently, this study investigates the determinants of tendering outcomes in Homa Bay County’s public sector, with the goal of identifying actionable measures to strengthen transparency, accountability, and overall procurement performance.

1.2. Theoretical and Conceptual Framework

The Principal–Agent Theory, first articulated by Jensen and Meckling (1976), frames public governance as a relationship in which a principal delegates tasks to an agent whose actions should align with the principal’s objectives. Effective application of this theory requires principals to select agents with the right capabilities and incentive structures, then monitor outputs to mitigate issues arising from asymmetric information—namely moral hazard and adverse selection (Leruth & Paul, 2008; Gailmard, 2012; Ballwieser et al., 2012). In public service delivery, conflicting priorities among officials, citizens, and contractors further complicate these dynamics (Kamara, Ofori-Owusu, & Sesay, 2012). Governance models invert these roles: in bottom-up systems, citizens act as principals and politicians as agents, whereas in top-down structures public bodies serve as agents to the government while simultaneously acting as principals over service managers (Whipple & Roh, 2010; Podrug, Filipovic, & Milic, 2011). To foster accountability, the theory suggests that agents—public managers—should have incentives to disclose information voluntarily, enabling principals to monitor performance and reduce opportunistic behavior (Lambright, 2008).

The New Public Management (NPM) Theory emerged with Hood’s (1991) call to import private-sector control and efficiency into government, advocating for performance management, cost-effectiveness, and responsiveness (Hughes, 2012). Influenced by public choice and managerialism, NPM promotes market-style mechanisms—such as competitive procurement, outsourcing, and decentralization—to improve service delivery and value for public funds (Diefenbach, 2009; Groot & Budding, 2008; Simonet, 2011). Its key features include e-government platforms, transparent procurement processes, and rigorous performance measurement (Zungura, 2014; Van Waarden & Van Kersbergen, 2009). By emphasizing customer responsiveness, entrepreneurial leadership, and social accountability, NPM informs practices in tendering, contract management, and stakeholder engagement, highlighting how market-based incentives can drive efficiency and enhance citizen satisfaction in the public sector (Gumede & Dipholo, 2014; Cohen, 2016; Mongkol, 2011)..

The variables of the study consisted of one dependent variable (procurement performance) and three independent variables (price and promotion of local bidders)

2.1. Empirical Literature

2.1.1. Influence of Price on Procurement Performance

Across the United Kingdom, Argentina, China, and Saudi Arabia, mixed-method and quantitative studies consistently demonstrate that price considerations play a pivotal role in shaping procurement performance. In the UK, collaborative relationships with suppliers—fostered through transparent communication and trust—were shown to optimize cost efficiencies and drive innovation in tendering practices (Ellram & Fugate, 2019). Smith’s work in Argentina similarly underscored the importance of transparency and fair competition among bidders for achieving value for money, though its purposive sampling risked overlooking some stakeholder perspectives (Smith, 2020). In China, continuous process improvement emerged as a key enabler of sustained cost savings and supplier relationship management, highlighting the value of innovation cultures even when systematic sampling may bias against skewed populations (Chen & Wang, 2019). Likewise, studies in Saudi Arabia found that organizational characteristics—such as firm size and technology adoption—moderate the price–performance link, with stratified approaches revealing industry-specific dynamics (Mahmoud & Khan, 2020).

In Ghana and Nigeria, researchers have explored how transactional costs, competitive tendering, and risk management intersect with price to influence procurement outcomes. Ofori and Dadze (2024) showed that lower transactional costs and rigorous tender processes significantly boost procurement performance, though their reliance on purposive sampling may have limited generalizability. Adeleke and Ogunyemi (2019) confirmed that transparency, accountability, and robust risk practices underpin the effective management of price, using stratified sampling to capture diverse firm profiles but facing challenges in defining population strata. These studies collectively affirm that price is not simply a bidding variable but a strategic lever that—when coupled with sound governance and risk mitigation—drives efficiency and value creation across West African procurement contexts.

In Kenya, investigations at both county and state levels further illuminate price’s strategic importance. Kisurkat (2016) reported that tendering delays impede organizational performance in Kajiado County, while Nganu and Mwangangi (2019) found that relationship management and strategic sourcing enhance value for state corporations, emphasizing procurement methods beyond mere price competition. Mwangi (2021) demonstrated that cost-optimization practices predict manufacturing-firm performance in Nairobi County, underscoring price’s role in resource allocation and resilience. Together, these Kenyan studies highlight price as a fundamental determinant of procurement success—enabling efficient resource use, improving supplier relationships, and fostering transparency—while also pointing to the need for sampling approaches (such as simple random sampling) that ensure broad stakeholder representation and robust, generalizable insights..

2.1.2. Influence of Promotion of Local Traders on Procurement Performance

Research across diverse contexts shows that actively promoting local businesses within public procurement consistently enhances cost-effectiveness, operational efficiency, and broader socio-economic outcomes. In France, mixed-method evidence demonstrates that transparent engagement with local suppliers yields mutual benefits—lower costs, innovation, and social impact—though reliance on document analysis can introduce bias (Brown & Garcia, 2020). Similar quantitative findings emerge from Brazil and Iran, where stratified random sampling and structured questionnaires reveal that local-bidder initiatives drive job creation and economic growth, despite capacity and quality constraints that require careful policy design (Pereira & Costa, 2020; Mohammadi & Ahmad, 2020). Studies in Malaysia and Egypt further underscore the importance of stakeholder collaboration and robust sampling strategies to strengthen generalizability and ensure that small-scale innovations translate into lasting community development (Aung, Bhaumik & Chakkaravarthy, 2023; Ibrahim, 2019).

In the broader African procurement landscape, rigorous planning, interpersonal skills, and digital integration emerge as critical enablers of performance. Rwandan evidence indicates that structured monitoring and iterative learning bolster organizational outcomes, though universal sampling limits representativeness (Mbonimana, Akumuntu & Rugamba, 2021). In Tanzania, heads of government authorities report that strong interpersonal competencies and cross-functional coordination significantly elevate user satisfaction—linking compliance with tendering practices to improved procurement results (Mushi, Ismail & Mchopa, 2024). South African SMEs further illustrate that e-procurement and seamless supplier integration drive both tangible and intangible gains in supply-chain performance, highlighting digital tools’ transformative potential across sectors (Mafini, Dhurup & Madzimure, 2020).

Kenyan studies reinforce these themes while highlighting local governance dynamics. Research on state corporations shows that robust supplier relationships and end-to-end process management elevate service delivery, suggesting that inclusivity in data collection—by surveying both procurement officers and suppliers—yields richer insights (Otieno & Shale, 2019). County-level analyses in Siaya underscore the primacy of clear selection criteria and quality standards in tendering, whereas earlier work reveals that favoritism, tribalism, and nepotism remain systemic challenges (Amoke, Arani & Otieno, 2024; Ayoti, 2012). Taken together, these findings affirm that integrating local traders fosters economic development, supply-chain resilience, and stakeholder satisfaction—guiding the present study’s focus on optimizing procurement practices in Homa Bay County.

3.1. Research Methodology

The study employed a descriptive survey research design—a systematic plan for generating answers to the research problem by collecting and analyzing data on current conditions and relationships (Kombo & Tromp, 2011; Mugenda & Mugenda, 2003)—targeting a population of 117 procurement stakeholders drawn from six Homa Bay County government departments (Mugenda & Mugenda, 2005; Kothari, 2005). To ensure representativeness across these strata, stratified random sampling was used, with each department forming a stratum and sample size calculated via Israel’s formula for 95% confidence (Israel, 2010), yielding 91 respondents distributed proportionally across procurement, executive, finance, public works, health, and human resources offices. Data were gathered through a structured questionnaire with Likert-scale items, designed in three parts to capture demographics, tender-award practices, and procurement performance, and piloted on 12 non-study participants (10% of the sample as recommended by Connelly, 2018) via a re-test method over two weeks, which produced a high reliability coefficient of 0.89 (Glen, 2016; Creswell, 1999). Face and content validity were established through expert review in procurement and logistics departments (Prince & Jhangiani, 2015), and collected responses were analyzed using linear regression models to examine hypothesized relationships (Kothari, 2003).. The model is represented as follows:

Y=α+β1X1+ β2X2+ε

Where;
Y is the Performance of procurement function, α is the autonomous constant, β is the slope of the equation, and ε is the error with independent variables X1, X2 described as follows:
X1 is the influence of price measured as the cumulative influence of tender warding consideration;
X2 is the influence of promotion of local bidders measured as the indicators influencing tender awarding consideration.

4.1. Findings And Discussion of Results

The total number of questionnaires distributed to respondents was 91, out of which 84 questionnaires were fully completed and returned for analysis. This represents a 92.3% response rate, which is considered highly acceptable and indicative of robust data collection.

4.1.1. Descriptive Statistics for Price

The descriptive analysis of price’s influence on procurement performance reveals a generally moderate emphasis on pricing factors. Respondents most strongly agreed that staff are sensitized to value-for-money considerations when making purchases (mean = 4.01, SD = 0.543), indicating widespread awareness of cost-effectiveness principles. Measuring the quality of procurement records to enhance price achieved a solid but lower mean (3.66, SD = 1.031), suggesting room for standardization in record-keeping practices. Transparency in the procurement process (3.06, SD = 0.782) and the notion that selecting the lowest bidder serves as motivation (3.02, SD = 0.550) received the weakest agreement, highlighting opportunities to bolster fair-pricing safeguards and to evaluate the motivational efficacy of lowest-price awards. Finally, basing selections on supplier performance and value scored a mean of 3.12 (SD = 0.468), reflecting consistent but moderate application of performance-based criteria in award decision.

4.1.2. Descriptive Statistics for Price Promotion of Local Bidders

The study results were presented on Table 2. Respondents indicate that promoting local bidders has mixed effects on procurement performance. There is fairly strong agreement that local suppliers receive priority when tenders are advertised (mean = 3.84, SD = 0.91) and that they participate effectively in available local tenders (mean = 3.56, SD = 0.82), suggesting that the policy of giving preference to home-grown vendors is both visible and operational. By contrast, the items addressing broader supplier-market benefits—enhancing supplier diversity and competition (mean = 2.64, SD = 0.81) and strengthening ongoing relationships with local vendors (mean = 2.36, SD = 0.75)—score substantially lower, indicating that while local firms do win and engage in bids, efforts to broaden the supplier base and deepen collaborative partnerships remain underdeveloped. Overall, these results point to successful priority-setting for local bidders but signal a need for more proactive strategies around market diversification and relationship management.

4.1.3. Correlation Analysis

Findings in Table 3 shows that there is a significant positive relationship (r = 0.784) between price and lead time. This suggests that as value for money increases, lead time tends to increase as well. This finding is supported by Madara and Njenga (2022) study in Kenya that found that tendering process had influence on financial management. The finding also shows that there is a significant positive relationship (r = 0.807) between promotion of local bidders and procurement performance. This indicates that promoting local bidders tends to positively impact procurement performance. This finding is in line with that of Mafini, Dhurup and Madzimure (2020) study in South Africa that found that integration of local suppliers exerts positive linear relationship with both the tangible and intangible dimensions of supply chain performance. Further, Aung, Bhaunik and Chakkaravarthy (2023) study in Malaysia found that good procurement practices positively impact supplier relations and procurement performance.

*. Correlation is significant at the 0.05 level (2-tailed).
**. Correlation is significant at the 0.01 level (2-tailed).

4.1.4. Regression Analysis

Table 4 shows that regression analysis revealed a significant positive relationship between the dependent variable (performance of procurement function) and the independent variables (price, promotion for local bidders, accountability and lead-time). This indicates that as the independent variables increase, the performance of the procurement function also increases. The coefficient of determination, denoted as R square, was found to be 0.757. This value suggests that approximately 75.7% of the variability in the performance of the procurement function can be explained by the independent variables (price, promotion for local bidders, accountability, and lead-time on performance). In other words, these independent variables collectively account for a significant portion of the observed variation in procurement function performance.

a. Predictors: (Constant), price, promotion for local bidders, accountability, and lead-time.

Table 5 shows that Analysis of variance predicts positive influence of tender awarding practices on performance of procurement function. The regression model as a whole is statistically significant (F = 5.298, p < .0001), indicating that at least one of the predictors significantly contributes to explaining the variance in the dependent variable. The residual sum of squares represents the unexplained variance in the dependent variable. The total sum of squares represents the total variance in the dependent variable

a. Dependent Variable: Performance of Procurement Function
b. Predictors: (Constant), price, promotion for local bidders, accountability and lead-time.

Model above reaches statistical significance (Sig = .000, thus p<.0005). By checking the value in the column marked Sig. each of the independent variables above to determine whether it’s making a statistically significant unique contribution to the equation. Thus, all the predictor variables, price, promotion of local bidders, accountability, and lead-time made a unique, statistically significant contribution to the prediction of performance of procurement function, since Sig. <0.0005. The intercept represents the estimated value of the dependent variable when all predictor variables are zero. In this case, it is 3.542 with a standard error of .341 and a significant t-value (t = 4.402, p < .0001). The coefficient indicates that for every unit increase in price predictor, there is a corresponding increase of .050 in the dependent variable, holding other predictors constant. It has a significant standardized coefficient (Beta = .107, p = .010).

Similarly, for promotion for Local Bidders, every unit increase in the promotion for local bidders’ predictor, there is a corresponding increase of .227 in the dependent variable, holding other predictors constant. It has a significant standardized coefficient (Beta = .425, p < .0001). This finding is supported by that by Otieno and Shale (2019) study in Kenya tha found that supplier relationship ensures high level of service delivery.

a) redictors: (Constant), Price, promotion for local bidders, accountability, lead-time.
b) Dependent Variable: Performance of Procurement Function

5.1. Conclusions and Recommendations

The findings of the study collectively emphasize the significance of various factors, including price, promotion of local bidders, accountability, and lead time, in influencing procurement function performance within the context of Homa Bay County Government. These factors play pivotal roles in shaping the efficiency, effectiveness, and overall success of procurement processes. Based on the findings, it is recommended that Homa Bay County Government prioritize efforts to enhance price considerations, promote local bidders' participation, strengthen accountability mechanisms, and improve lead time management within its procurement processes. This can be achieved through the implementation of targeted policies, capacity building initiatives, and technological solutions aimed at streamlining procurement procedures and optimizing resource utilization. In addition, the study recommends that procurement functions in County Governments should promote local bidders. The local bidders represent the local organizations and therefore once they are promoted there would be employment opportunities created hence improving living standards.

6.1. Further Study Recommendations

Expanding upon the current study's findings and implications, several avenues for further research emerge that could deepen our understanding of procurement practices and performance within government entities. Further investigation could focus on identifying and addressing the challenges associated with the implementation of procurement policies and practices. Understanding the barriers faced by procurement officers and other stakeholders in effectively executing procurement processes could inform the development of targeted interventions to improve performance. With the increasing digitization of procurement processes, there is a need to examine the impact of technology adoption on procurement function performance. Research could explore how the use of e-procurement systems, digital platforms, and automation tools influences efficiency, transparency, and accountability in procurement operations. Conducting comparative studies across different jurisdictions or countries could offer valuable comparative insights into procurement practices and performance. Comparative analysis could explore variations in procurement regulations, practices, and outcomes, shedding light on best practices and lessons learned that could inform policy development and implementation.

References