Impact of Monitoring and Evaluation System Factors on Labour Force Management Practices Among Indigenous Construction Firms' Projects in Ghana.

Engineering and Technology Journal e-ISSN: 2456-3358 Volume 10 Issue 12 December-2025, Page No.- 8247-8262 DOI: 10.47191/etj/v10i12.25, I.F. – 8.482 © 2025, ETJ 8247 ETJ Volume 10 Issue 12 December 2025 , 1 John Yanyi Ampah Impact of Monitoring and Evaluation System Factors on Labour Force Management Practices Among Indigenous Construction Firms’ Projects in Ghana. John Yanyi Ampah1, Clinton Aigbavboa2, Zakari Mustapha1, 1 Department of Civil Engineering & Construction Technology Management, Cape Coast Technical University, P. O. Box DL 50, Cape Coast, Ghana. 2Department of Construction Management and Quantity Surveying, University of Johannesburg, South Africa. ABSTRACT: The Monitoring and Evaluation System (MES) is part of the life cycle of a construction project, which aids in tracking labour job performance and productivity at any given time, as well as provides reasons for any observed project position. It is also a project management function. This study aimed to determine the impact of monitoring and evaluation system factors on labour force management practices in indigenous construction firms’ projects in Ghana. A questionnaire survey was used as the instrument for this study, and the respondents consisted of project managers, engineers, contractors, and consultants in the Ghanaian construction industry. The analysis was carried out using Exploratory Factor Analysis (EFA) and Structural Equation Modelling (SEM). The results showed that, the approach to M&E, M&E information system, Budgetary allocation for M&E, Stakeholder involvement in M&E, Technical capacity and training of the M&E team, Organisational guideline and capacity for M&E, M&E logical framework, Management skills in M&E, Evaluation of labour plan, Labour participation in the M&E process, and Labour plan implementation M&E are the most important factors that affect construction firms labour force management practices in Ghana. It was also gathered that M&E data quality and communication of M&E findings are acknowledged as crucial monitoring and evaluation system factors but with slightly lower average ratings. It can be concluded from the findings that, all the M&ESF considered in this study have a high influence on LFM practices in indigenous construction firms project delivery. Construction project managers and other relevant stakeholders should understand that these significant factors are likely to help the labour force perform extremely well when they use the principles of LFM in their various construction firms. Project managers and engineers should be responsible for creating an environment that can naturally foster M&ES in their labour force operations to enhance LFM practices and thereby achieve excellence in their construction firms. KEYWORDS: Labour force management, Monitoring and evaluation system factors, Construction firms, Ghana. I. INTRODUCTION The construction industry plays a critical role in the development of many countries’ economies. According to Mazhar and Arain (2015), the construction industry’s contribution to global GDP is estimated at around 15%. Given the industry's potential contribution to a country's economic development, it is imperative to ensure that resources and activities are managed effectively. This can only be achieved through an effective monitor-ing and evaluation system that measures job performance and project productivity throughout the life cycle of a project (Tengan & Aigbavboa, 2018). Several infrastructure projects initiated by most developing countries have failed for various reasons, including ineffective monitoring and evaluation systems (Kissi et al., 2019; Yu et al., 2018). To ensure the successful execution of construction firms' projects, monitoring and evaluation systems must be implemented holistically throughout the project life cycle. The influence of monitoring and evaluation on project success is not correlated with the practice of monitoring and evaluation of construction projects (Chan et al., 2019; Polat & Demirkesen, 2024). Therefore, little attention has been given to the monitoring and evaluation system as a management practice, despite the overwhelming evidence of its contribution to the execution of construction projects. (Kissi et al., 2019; Umar et al., 2024) also found that M&E is vital to the successful management of construction projects. Decades ago, M&E practices were determined by emphasizing prudent utilisation of resources (Huzooree & Yadav, 2025; Rehan et al., 2024). However, many firms, as well as project managers in the modern era, regard M&E practices as a requirement for success rather than a management tool for project appraisals and for identifying and correcting problems in project planning and implementation (Kissi et al., 2019; Sajjad et al., 2023). MES aims to improve the efficiency and effectiveness of construction projects (Menon, 2024; Ovcina & ArslanagicKalajdzic, 2024). It is asserted that M&E is one of the most relevant tools that influence the performance and successful “Impact of Monitoring and Evaluation System Factors on Labour Force Management Practices Among Indigenous Construction Firms’ Projects in Ghana.” 8248 ETJ Volume 10 Issue 12 December 2025 , 1 John Yanyi Ampah completion of construction projects (Lee et al., 2020; Naji et al., 2024). Anjomshoa (2024) and Lazari et al. (2024) posit that M&E relates to the value or significance of an activity, policy, or programme. Moreover, as stated by the Organisation for Economic Cooperation and Development (2010), monitoring is an ongoing activity that involves the systematic gathering of data on specific indicators (Anjomshoa, 2024; Lazari et al., 2024). This process aims to provide key stakeholders in a current project with insights into progress and goal achievement. Also, evaluation refers to a systematic and objective assessment of an ongoing or completed project (OECD, 2010). Further, the poor understanding of the role of the two management functions, “Monitoring” and “Evaluation,” can be blamed for the poor job performance and productivity of construction firms in developing countries (Garcés et al., 2025; Ghaly et al., 2024; Ghobakhloo et al., 2023). Similarly, the introduction of monitoring and evaluation across various business sectors has led to occasional misunderstandings regarding the specific factors of these systems in construction project management. In light of this, this study, through a literature review of pertinent databases, elucidates the impact of monitoring and evaluation system factors on LFM practices among indigenous construction firms’ projects in Ghana. Statement of the Problem The monitoring and evaluation system is the sole project activity that spans all stages of construction projects' life cycles, helping ensure that the project's progress remains on course. The concept of systematic M&E among construction firms is often sidelined, and focus is instead given to other areas of project management, such as initiation, planning, implementation, and closeout (Aigbavboa, 2018; Dahalan et al., 2023; Ovcina & Arslanagic-Kalajdzic, 2024). Alcock (2009), Armstrong and Baron (2013), and Naidoo (2011) contend that a well-implemented monitoring and evaluation system enables project managers to make informed decisions about ongoing projects, thereby contributing to the success of construction firms. (Nguyen et al., 2024; Umar et al., 2024). Furthermore, indigenous construction firms in Ghana are mandated to carry out both civil and building construction projects. These construction firms primarily struggle with a lack of understanding of the essential elements needed for those involved in the monitoring and evaluation of projects. Top management does not grasp the significance of monitoring and evaluation factors in construction projects. Consequently, they have not established institutional monitoring or evaluation systems. This indicates that while significant progress has been made in delivering construction projects to clients in Ghana, there remains a substantial need for training, workshops, and discussions on M&ES. Additionally, appropriate M&ES must be implemented at the level of indigenous construction firms to improve the delivery of projects. The frequent failures of construction projects prompted this research to assess how M&ES factors influence labour force management practices within indigenous Ghanaians construction firms’ projects delivery. The objectives  To assess the monitoring and evaluation system factors on labour force management practices of indigenous construction firms in Ghana.  To determine the effect of monitoring and evaluation system factors on LFM practices of indigenous construction firms. II. LITERATURE REVIEW The concept of monitoring and evaluation (M&E) The origins of M&E are rooted in perceptions of public-sector failures as early as the 1950s (Alizadehsalehi & Yitmen, 2018; Cameron, 1993). Nevertheless, the idea of assessment was discussed in the USA in the 1960s and 1970s, when the state helped fight poverty through the War on Poverty and the Great Society (Lan et al., 2024; Medina‐Muñoz & Medina‐ Muñoz, 2019; Waithera & Wanyoike, 2015). Some projects underperformed (failed), leading to the creation of an independent M&ES unit with responsibilities ranging from collecting data to pro-cessing and analysing it (Huang et al., 2022; Z. Liu & Wang, 2023). The M&E departments were tasked with reporting on project performance relative to the initial targets to both ministries and international agencies. M&E is not a novel concept and has been present in various fields of study and practice, including finance, governance, agriculture, development projects, and health. The focus of M&E has been on accountability and systematic social enquiry, which are central to evaluation research (Egbon, 2024; Hamal et al., 2018; Rahman, 2021). Although the profession is well established and there is existing literature on the subject, the ultimate goal and impact on project delivery remain questionable, as projects often fail to meet quality standards, experience cost overruns, are completed later than planned, and result in overall dissatisfaction among project participants. Project management, as a function of M&E, is among the major drivers of project success. As noted by Kamau and Mohamed (2015), M&E is a critical success factor in project delivery. Achieving project success is nearly impos-sible without continuous M&E, consistent with the literature and practice (Menon, 2024; Ovcina & ArslanagicKalajdzic, 2024; Sohal et al., 2022; Kamau & Mohamed, 2015). Kibebe and Mwirigi (2014) ranked ineffective M&E as the top management factor contributing to project failure (Khodabakhshian et al., 2023; Menon, 2024; Nuako et al., 2024). The latter emphasises the importance of monitoring and evaluation in the construction sector. While monitoring and evaluation are two managerial tasks performed closely together to achieve a project's objectives, there are differing opinions regarding their relationship. Whereas M&E are seen as two separate functions by many evaluation schol-ars, others have argued the inseparable nature of the two management functions (Animashaun et al., 2024; Kissi et al., “Impact of Monitoring and Evaluation System Factors on Labour Force Management Practices Among Indigenous Construction Firms’ Projects in Ghana.” 8249 ETJ Volume 10 Issue 12 December 2025 , 1 John Yanyi Ampah 2019; Varajão & Trigo, 2024; Musomba et al., 2013; Omonyo, 2015). Furthermore, the monitoring and evaluation system (M&ES) has become essential for ensuring successful project execution in construction firms. Owing to the varied interpretations and perceptions of construction M&ES, this study provides a theoretical understanding of M&E in the construction context. This highlights the significance of M&E in achieving successful project outcomes for construction firms. This understanding forms the core of formulating actions that can be put forward to enable project teams to set M&E in motion seriously and conclusively to enhance job performance and productivity. Existing studies across various domains have underscored the imperative role of M&E in achieving project success (Kissi et al., 2019; Qureshi et al., 2021; Salzano et al., 2024; Umar et al., 2024; Varajão & Trigo, 2024; Kamau & Mohamed, 2015). From a theoretical standpoint, the concept of M&E has been interpreted and defined in various ways. The absence of a consistent definition for M&E continues to pose a significant challenge in the literature (Dong et al., 2024; Ovcina & ArslanagicKalajdzic, 2024; Sreedharan V & Sunder M, 2018; Patton, 2003). To gain a deeper understanding of the diverse and complementary nature of M&E in the context of project delivery within construction firms, this study delineates M&E functions separately. It highlights the distinctions between these two management roles and emphasises their contributions to the success of the firm’s projects. Monitoring Monitoring is a continuous management function that logically collects data on specific indicators of the project to offer management and stakeholders of an ongoing intervention the indications of the extent to which objectives are being achieved and the progress in the use of the allocated resources (Bangladesh, 2024; Dugbartey & Kehinde, 2025; Ebirim, Usman, et al., 2024) (Omonyo, 2015). Whereas Gudda (2011) described monitoring as an art of collecting project infor-mation to make an informed decision at the right time (Bondar et al., 2024; B. Liu et al., 2024), and Kitchens et al. (2024) defined monitoring as an ongoing process of generating information about the progress being made towards the achievement of results. According to Bamberger and Hewitt (1986), monitoring is an internal project activity designed to provide continuous feedback on progress and the efficiency with which it is being implemented (Animashaun et al., 2024; Ebirim, Olu-Lawal, et al., 2024; Nuche et al., 2024). Monitoring is also applied during project implementation to ensure that the design and operations of the project are enhanced as it progresses. Animashaun et al. (2024) and Ebm et al. (2024) emphasise that monitoring assesses stakeholders' understanding of the project, promotes systematic and professional management, minimises the risk of project failure, and finally assesses progress in implementation. Abikoye et al. (2024) and Albert et al. (2023) indicate that the World Bank came into the picture by agreeing that several descriptions had been provided about monitoring and further defined monitoring as a constant evaluation of project execution with respect to the agreed work schedule, input, infrastructure, and services consumption by the beneficiaries. Chipato (2016) identified monitoring as the ongoing process by which stakeholders receive regular feedback on progress towards achieving their goals and objectives. Chipato (2016) further stressed that monitoring implies a continuing opera-tion conducted during project implementation to ensure that the project remains on track to achieve its objectives. The mon-itoring exercise may be used to improve project effectiveness during implementation: the project should be flexible and able to adapt to conditions on the ground, as indicated by the exercise (Chipato, 2016). Monitoring is carried out once a program is already being implemented and continues throughout the program implementation period. Monitoring is sometimes referred to as process, performance, or formative evaluation (Amaechi et al., 2022; Wiefek et al., 2024). The three types of monitoring In monitoring research, two researchers (Tache 2011) have identified various types of monitoring and classified monitoring into three generic categories: 1). Baseline monitoring 2). Impact monitoring and 3). Compliance monitoring. Baseline monitoring is the value of measuring economic, social, and environmental needs prior to a project to determine existing conditions, levels of variation, and the change process. Impact monitoring is the measurement of social and environmental variables during project development and operations to determine the impact which could have occurred due to the project. Monitoring compliance involves assessing compliance with donor rules, contract terms, local Western regulations, building by-laws, and ethical standards in providing the undertaking. Another similarity between (Li et al., 2022) is the division of monitoring into three groups: 1) Process or activity-based monitoring, 2). Outcome-based monitoring 3). Implementation monitoring. Process or activity-based monitoring involves executing tasks to meet time and budgetary goals. However, it falls short of connecting these tasks to outcomes, making it difficult to determine how they contribute to enhanced performance. It also monitors the consumption of resources and inputs, the flow of activities, and the output delivery. It monitors the manner in which activities are provided in terms of efficiency in time and resources. To connect with monitoring the overall aim of a project and its impact on society, that is, resultsbased monitoring. This type of monitoring integrates M&E to ensure that projects can achieve their intended results. It is recognised for its comprehensive approach, which aligns “Impact of Monitoring and Evaluation System Factors on Labour Force Management Practices Among Indigenous Construction Firms’ Projects in Ghana.” 8250 ETJ Volume 10 Issue 12 December 2025 , 1 John Yanyi Ampah activities, processes, inputs, and outputs with desired outcomes. This method is often described as the ideal form of monitoring. Implementation monitoring concerns the monitoring of the methods to be used in project delivery to achieve the desired results. This is to ensure that correct inputs and activities are employed in the production of output and compliance, which can result in a set output. Thus, monitoring will focus on resources, activities, goals (results, purpose development goal), and basic assumptions. Evaluation The term “evaluation” refers to the objective, systematic assessment of project activities to determine their relevance, effectiveness, efficiency, and impact (Gong et al., 2021). Project evaluation plays a significant role in project implementation; it informs decision-making for improvement, ensures organizational learning from experience to improve future monitoring and evaluation practice, and helps managers acquire new skills to be better managers in the future (Njama, 2015). Stufflebeam and Moradi et al. (2020) state that one of the earliest and still most prominent definitions states that it means determining whether objectives have been achieved. Evaluation also helps organisations understand their strengths, weaknesses, opportunities, and threats (SWOT) for effective M&E (Ghaleb, 2024; Rony et al., 2024). Furthermore, evaluation establishes benchmarks to guide the evaluation of other projects by creating a knowledge bank for management, thereby fostering organizational learning (Alsakarneh et al., 2024). Evaluation provides the basis for concluding the efficiency, effectiveness, and success or failure of projects (Agrawal et al., 2020; Alsakarneh et al., 2024). Evaluation is arguably society’s most fundamental discipline, as it is oriented towards assessing and improving society as a whole (A. Garro & F. Barrara, 2024). They also defined evaluation as a method for providing testimony on issues such as reliability, effectiveness, cost-effectiveness, efficiency, safety, ease of use, and probity. Evaluations may involve assessing the extent to which objectives have been met, drawing on data and information generated through monitoring (Sagharidooz et al., 2024). In carrying out an evaluation, the evaluator needs to pay attention to the evaluation’s root term value in addressing the merit, worth, probity, and significance regarding excellence, utility, uncompromising adherence to the basic moral standards, reach, importance, and visibility of the project (Jankalová & Jankal, 2018; Kportorgbi et al., 2024). More specifically, evaluation is a process of delineating, obtaining, reporting, and applying descriptive and judgmental information about an object’s merit, worth, probity, and significance (Teasdale, 2021). The three types of evaluation Evaluation can be classified into several types depending on the intended purpose or stage of implementation (Omonyo, 2015). Considering the timing of the evaluation, three types of evaluation exist according to Tache (2011) and Gudda (2011), they are 1). Ex-ante evaluation in-2). Vivo or mid-term evaluation and 3). Ex-post evaluation. Ex-ante evaluation refers to an assessment conducted before the commencement of a project. In vivo or mid-term evaluations are conducted during the project's execution phase. This type of evaluation is formative and can be repeated as needed to provide the required information. The final evaluation, conducted only after a project's implementation, is a summative assessment typically carried out by external evaluators. Ex-post evaluation, conducted after the final evaluation, aims to assess a project's sustainability or its impact on the community benefiting from it. Other classifications are based on the implementers or those responsible for the evaluation, namely, whether the evaluation is undertaken internally by persons directly involved with the project or externally by stakeholders and donor agencies (Barriga & Escandon‐Barbosa, 2024; Rumanti et al., 2021). Learning from evaluation then extends beyond organizational learning; it also encompasses advancing knowledge in development (Fonseca et al., 2024; UNDP, 2009). firm’s labour force The Monitoring and Evaluation System is a process that, by influencing the outcomes of a project, enables construction project managers to improve labour performance and productivity levels within a firm. M&ES of the construction labour force is known as an inevitable management operation. It is useful for monitoring the functioning of a labour force. It also provides frequent reports on the labour force, including their delivery and targeted outputs. The monitoring and evaluation system is an important aspect of job performance and labour force productivity. Through monitoring and evaluation systems, information is collected and analysed to track the progress of labour force work (Calvetti et al., 2020; Gazi et al., 2024). Monitoring and evaluation systems involve the routine collection and analysis of information to track the progress of the labour force (Nwaogu et al., 2019; Riau et al., 2024). Again, Aghimien et al. (2021) and Manoharan et al. (2020) outline the key monitoring and evaluation activities in a construction firm. They involve a preliminary needs assessment, system planning for monitoring and evaluation, and baseline studies. It also stated that monitoring and evaluation require attention to the use of the labour force and the efficiency of project implementation to ensure that the quality of the construction project meets the goals set. Ebirim, Usman, et al. (2024) established that management in construction firms should be able to identify the purpose and scope of the M&E system, plan for information reporting and utilisation, collect and manage data, analyse data, and monitor and build the capacity of the labour force. Tasheva and Karpovich (2024) showed that knowledge of monitoring “Impact of Monitoring and Evaluation System Factors on Labour Force Management Practices Among Indigenous Construction Firms’ Projects in Ghana.” 8251 ETJ Volume 10 Issue 12 December 2025 , 1 John Yanyi Ampah and evaluation helps management effectively monitor and evaluate the labour force, thereby improving a firm's job performance and productivity. Further, Bhat and Sheikh, (2024) and Mustafa and Lleshi, (2024) studies established the constraints and problems that hamper the monitoring and evaluation of labour force work, including a lack of commitment to conducting monitoring and evaluation, discussing, sharing, and incorporating the results of monitoring and evaluation activities, shortage of trained staff, insufficient technical resources, inadequate allocation of funds for monitoring and evaluation, and limited training opportunities, which usually execute construction projects. The benefits of monitoring and evaluation system of construction firms’ projects Studies have shown a plethora of benefits derived from an effective monitoring and evaluation system of construction projects (Kamau & Mohamed, 2015; Otieno, 2000; Tache, 2011). The aim of implementing monitoring and evaluation is to guarantee the ultimate success of a project by achieving short-term goals, such as adherence to standards and meeting budget and schedule requirements, as well as long-term goals, such as ensuring that the project is fit for its intended purpose (impact). The collective achievement of all immediate out-comes indicates that M&E is effective, and therefore, the project is successful (Lagos & Alarcón, 2021; Umar et al., 2024). Ebekozien (2021) revealed that conformity to project specifications (qual-ity) is achieved when projects are effectively monitored and evaluated. The study further accentuates the achievement of projects within the approved budget (cost) and project duration (time) when M&ES is effectively undertaken (Ebekozien, 2021). Good project M&E practice creates a healthy project environment for implementation, ensuring that all stakeholders are well represented and given a chance to be part of the project. Project resources are scarce and should be used prudently. An even more valuable advantage of good M&ES is the knowledge that project activities are being performed correctly the first time, thereby avoiding rework (which is the probable net cause of project budget and schedule overruns) due to design and construction malfunctions. In addition, the result of M&ES activities is enhanced communication among various stakeholders. This provides stakeholders with a superior understanding of implementation concerns about every aspect of the undertaking. An environment where effective communication can take place and dialogue can continue is constructive. Establishing transparent and accessible communication channels, such as regular meetings, workshops, and dissemination of information via the Internet or print media, is essential. From this, it can be deduced that the hallmarks of a successful project, such as timely completion, adherence to standards, cost management, stakeholder contentment, contractor efficiency, health and safety, value for money, environmental performance, enduser satisfaction, client approval, and the project's continued relevance, are achieved through effective implementation of M&ES construction projects. Theory of change The theory of change approach first emerged in the USA in the mid-1990s to improve evaluation theory and practice (Kissi et al., 2019; Umar et al., 2024; Stein & Valters, 2012). The theory of change not only sought to improve evaluation theory and practice but also evolved in response to the emphasis on outcomes and accountability placed by project and programme funders (Kabonga, 2019). This has placed much emphasis on the necessity of the theory of change. As postulated by Weiss (2004), the theory of change holds that a key reason a complex project fails is that its underlying expectations are poorly articu-lated (Omonyo, 2015; Hien et al., 2024; Zangana et al., 2024). Various definitions exist of what theory of change means across organisations in the evaluation field (Dombrowski et al., 2021). A theory of change is a critical thinking product or process that provides a broad view of the initial and intermediate changes required to reach a long-term goal. Bekius and Gomes (2023) asserted that the theory of change is a rigorous, participatory process for planning a project's long-term goals with stakeholders through the identification of interventions believed to lead to the achievement of the project's long-term objective. In other descriptions, Bekius & Gomes (2023) argued that a theory of change is a set of philosophies that describe the expected change, how the process will unfold, what drives it, and what must be done to achieve the intended results. He also considers this to be the envious role of project stakeholders. Therefore, the theory of change can be explained as an assumption about how direct interventions contribute to achieving project success (Ignatius Teye Buertey, 2016). The theory of change approach has been adopted in many fields, predominantly by international non-governmental organisations for evaluation purposes (Ignatius Teye Buertey, 2016). Program theory The program theory of evaluation has increased in utilisation over the last 10 years. It determines whether a program is planned in a manner that it can deliver the results it is supposed to deliver. Program theory is a guidance theory in project evaluation because it demonstrates a program's ability to address specific issues in projects that require evaluation (Eyieyien et al., 2024). It also provides guidance on the areas that should be emphasized during the evaluation process (Chen, 2015). Program theory is utilised in this study because it provides information that can lead to additional insights into how management affects M&E during project execution. This theory can be effectively employed whenever necessary to provide solutions and alternative steps to achieve the desired outcomes for projects that require evaluations. Additionally, it can improve decision-making and broaden understanding of solutions to project-related issues “Impact of Monitoring and Evaluation System Factors on Labour Force Management Practices Among Indigenous Construction Firms’ Projects in Ghana.” 8252 ETJ Volume 10 Issue 12 December 2025 , 1 John Yanyi Ampah (Animashaun et al., 2024; Kissi et al., 2019; Kabongo et al., 2020). III. METHODOLOGY Research is the methodical and data-supported pursuit of a response to questions, solutions to a problem, or a better understanding of an occurrence (Johnson et al., 2022, Kabir, 2016). A quantitative research approach was used to examine numerical data through statistical procedures for this study the reason is according to Creswell (2014) and Carcary (2020), a quantitative research approach should be used to examine numerical data through statistical procedures. In this study, a nonprobabilistic structured questionnaire survey was used to collect information from identified respondents of construction companies in Ghana. This approach was chosen to ensure that the research was easily answerable, unbiased, succinct, and straightforward to analyse (Khan et al., 2023). The study participants comprised a diverse group of professionals within the Ghanaian construction industry, including project managers, engineers, contractors, and consultants. Table 1 presents a summary of the respondents' demographic information, including gender, age, job roles, educational background, and work experience. These data are essential for comprehending the sample characteristics and interpreting the study results. Participants were asked to evaluate each factor using a fivepoint Likert scale, indicating their level of agreement or disagreement with factors such as the monitoring and evaluation system that affects LFM practices in Ghana's construction industry. A sample frame was created by compiling a list of reputable construction companies obtained from the Association of Building and Civil Engineering Contractors of Ghana (ABCECG). At the time of data collection, 1284 construction firms were registered and in good standing with the ABCECG. In this study, the goal was to sample 40% of the study population. This decision was informed by Leedy and Ormrod's recommendation, as cited in Leedy et al. (2010), which suggests that for a population of approximately 1500, at least 20% should be sampled. Therefore, a sample size of 514, which is 40% of 1284, was considered adequate for this study. Again, a probability sampling technique was used in this study to obtain representation from all segments of construction firms. A simple random sampling method was adopted, through which every member of the population had an equal chance of being selected (Kissi et al., 2024). For all these reasons, firms in Ghana, the nature, and composition of firms dictated the use of this sampling approach, and Tapera et al. (2020). supports that random sampling is suitable for such studies. The 514 questionnaires given to construction professionals in Ghana yielded a response rate of 91.82%, with 472 completed and returned. The data gathered were coded and examined using advanced statistical techniques. Various multivariate approaches were employed, including multivariate correlational analysis with EFA using SPSS version 26, structural equation modelling (SEM) using AMOS version 21, and confirmatory factor analysis (CFA). Additionally, the study elaborates on the statistical methods used to assess the validity and reliability of the measurement tool and the quantitative survey outcomes. This section begins with an evaluation of the participants’ demographic details. This was followed by scrutinising their responses to the specific objectives. Respondents’ backgrounds were analysed using frequency and percentage distribution. IV. FINDINGS This section outlines the empirical results obtained by analysing the survey data gathered from construction professionals in Ghana. The findings are divided into two primary sections: a descriptive analysis of the identified factors related to the M&E system and the results of multivariate statistical analyses. These analyses included the demographic characteristics of the study participants, EFA, CFA, and SEM. A. Demographic characteristics among the Study Participants The analysis of the demographic characteristics of the study participants revealed a nuanced profile of the respondents. The gender distribution indicated a predominant presence of males (68.9%), with females accounting for a sizable but lesser proportion (25.4%), and a smaller fraction chose not to disclose their gender (5.7%). The respondents spanned a broad age spectrum, with the highest representation in the 41 45 years bracket (37.9%), followed by individuals aged 46 years or older (17.2%), showcasing a mature and experienced cohort. Regarding occupation, the sample reflected a diverse labour force, prominently comprising civil engineers (38.1%), project managers (20.1%), and architects (15.3%). The educational qualifications exhibited a welleducated cohort, with a significant majority holding master’s (50.6 %) or bachelor’s (42.2 %) degrees, although those with doctoral degrees (PhD) constituted a smaller fraction (4.9%). Regarding professional experience, a notable portion of respondents had substantial work tenure, especially within the category of 31 or more years (33.9%), followed closely by the 2630 years category (24.6%). The firms which participated in the study predominantly engaged in civil engineering projects (51.5%), while the others engaged in building construction projects (48.5%). Past project experiences have varied. A significant proportion of firms have worked on seven or more projects (61.9%). Furthermore, insights into the firms’ demographics revealed a varied landscape, with firms existing for 2630 years (44.5%) and 31 or more years (34.1%) forming the majority. In terms of classification, the D3/K3 classification represented the largest segment (53.0%), followed by D4/K4 (26.3%). B. Descriptive Analysis of Monitoring and evaluation system factors “Impact of Monitoring and Evaluation System Factors on Labour Force Management Practices Among Indigenous Construction Firms’ Projects in Ghana.” 8253 ETJ Volume 10 Issue 12 December 2025 , 1 John Yanyi Ampah Table 2 provides a structured presentation of the findings related to the monitoring and evaluation system factors in Ghanaian construction firms. The Table 1. delves into monitoring and evaluation system factors (MESF), showcasing their perceived importance within organisational frameworks based on mean values and standard deviations. The factors related to the approach and information systems in Monitoring and Evaluation (M & E) processes, such as Approach to M & E and M & E information systems, received notably high mean ratings of 4.42 and 4.30, respectively. This collective agreement among respondents highlights the crucial role these elements play in effective monitoring and evaluation. While there are slight variations in perceptions, indicated by standard deviations of 0.866 and 0.823, the overall consensus underscores their critical contributions to the field. M & E data quality and communication of monitoring and evaluation findings, although slightly lower in mean scores at 3.93 and 3.92, respectively, are still recognised as significant contributors to robust monitoring and evaluation practices. The standard deviations of 0.887 and 0.818 suggest some diversity in opinions but an overall recognition of their importance in ensuring reliable M&E outcomes. Factors such as Budgetary allocation for monitoring and evaluation and stakeholder involvement in monitoring and evaluation received moderate to high mean ratings (4.13 and 3.96, respectively), signalling their perceived significance in the monitoring and evaluation landscape. However, the standard deviations of 0.793 and 0.910 indicate varying perspectives on their impact among the respondents. Other factors, such as technical capacity and training, organisational guidelines and capacity, and monitoring and evaluation logical framework garnered moderate mean ratings (ranging from 3.77 to 3.97), suggesting their perceived importance but with differing degrees of consensus among respondents. The standard deviations (ranging from 0.883 to 0.907) further highlight differing viewpoints regarding their direct influence on monitoring and evaluation effectiveness. Table 1: Monitoring and Evaluation System Factors (MESF) Variables Code Mean SD Approach to M & E MESF1 4.42 0.866 M & E information systems MESF2 4.30 0.823 M & E data quality MESF3 3.93 0.887 Communication of M & E findings MESF4 3.92 0.818 Budgetary allocation for M & E MESF5 4.13 0.793 Stakeholder involvement in M & E MESF6 3.96 0.910 Technical capacity and training of the M & E team MESF7 3.97 0.907 Organisational guidelines and capacity for M & E MESF8 3.88 0.896 M & E logical framework MESF9 3.77 0.903 Management skills in M & E MESF10 3.96 0.883 Labour participation in the M & E process MESF11 3.95 0.852 M & E of labour plans implementation MESF12 3.97 0.897 Table 2: Uni-dimensionality and Reliability of M&ES Factors Construct Variables MESF Corrected item-total correlation Squared multiple correlation Cronbach's Alpha if item is deleted Cronbach's Alpha Labour participation in the M & E process 0.689 0.392 0.386 0.834 0.838 Management skills in M & E 0.678 0.481 0.473 0.828 Stakeholder involvement in M & E 0.672 0.463 0.480 0.829 Organisational guidelines and capacity for M & E 0.651 0.524 0.445 0.824 M & E logical framework 0.637 0.428 0.236 0.831 Communication of M & E findings 0.615 0.567 0.411 0.821 Technical capacity and training of the M & E team 0.585 0.477 0.350 0.828 M & E information systems 0.564 0.548 0.348 0.822 M & E data quality 0.556 0.530 0.389 0.824 “Impact of Monitoring and Evaluation System Factors on Labour Force Management Practices Among Indigenous Construction Firms’ Projects in Ghana.” 8254 ETJ Volume 10 Issue 12 December 2025 , 1 John Yanyi Ampah M & E of labour plans implementation 0.538 0.576 0.430 0.820 Budgetary allocation for M & E 0.522 0.586 0.410 0.820 Approach to M & E Extraction method: Principal component analysis. A. 1 component extracted. An EFA was conducted to assess the unidimensionality and reliability of the Monitoring and Evaluation System Factors (MESF) construct. The extraction and rotation method employed was the maximum likelihood with varimax rotation (ML varimax). The construct was measured using 12 items. The KaiserMeyerOlkin (KMO) of 0.852 with Bartlett’s test of sphericity of p<0.000 was also obtained, indicating consistency with the recommended KMO cutoff value of 0.70 and Bartlett’s test of sphericity of p<0.05 suggested by Hair et al., (2010). The findings indicate that it is possible to perform factor analysis on the data. All 12 items (MESF1, MESF2, MESF3, …, MESF12) which were expected to measure Monitoring and Evaluation System Factors (MESF) loaded one component. Using a threshold of 0.5 for factor loading which is greater than the recommended value of 0.40 as suggested by Field (2005) and Hair et al. (1998), some of the items had their factor loading exceeding 0.5 for the respective component, excluding “Approach to M & E” which recorded a threshold below 0.5, making them a bad representative of the component. For the component, eleven (11) items recorded a threshold of more than 0.5. They are “Labour participation in The M & E process,” “Management skills in M & E,” “Stakeholder involvement in M & E,” “Organisational guidelines and capacity for M & E,” “M & E logical framework,” “Communication of M & E findings,” “Technical capacity and training of The M & E team,” “M & E information systems,” “M & E data quality,” “M & E of labour plans implementation, ” and “Budgetary allocation for M & E”. These items measure monitoring and evaluation system factors (MESF). Thus, they are called monitoring and evaluation system factors (MESF). After using the EFA to extract the component, the corrected itemtotal correlation for the items of the component was extracted using the suggested cutoff value of 0.30. It was found that the items were good measures of the components since the Cronbach’s alphas were greater than 0.800 at 0.838 for the component (MESF), indicating acceptable internal reliability (Nanually & Bernstein, 1994). After the constructs demonstrated sufficient evidence of unidimensionality and reliability using EFA, a CFA was administered. The analysis strategy of goodnessoffit for the Monitoring and evaluation system factors (MESF) followed a three statistics strategy of fit indexes as recommended by Hu and Bentler (1999). The sample data on the Monitoring and Evaluation System Factors (MESF) model yielded an S Bχ2 of 5.143 with 14 degrees of freedom (df) and a probability of p = 0.0000. This chisquare value indicates that the departure of the sample data from the postulated model was significant and hence, indicative of good fit. The chi square test is very sensitive to sample size and is used more as a descriptive index of fit than as a statistical test (Kline, 2005). The CFI value was determined to be 0.941, which was higher than the cutoff value of 0.90; thus, the model was acceptable. The NFI value was 0.928, which fell within the provided range; however, the provided cutoff value of NFI was NFI 90, as revealed in Table 8.39. Thus, the model is applicable. The PNFI value is 0.619, which is below the cutoff value of 0.80. The RMR of 0.036 is less than 0.05, and the GFI value of 0.958 is greater than 0.90. As shown in Table 2, the fit indices of the Monitoring and Evaluation System Factors (MESF) model indicated that the hypothesised model fit the data of the sampled population well and hence, can be considered in the complete analysis of the latent variable model (Table 2). Table 3: Robust Fit Index for MESF Fit Index Cut-Off Value Estimate Comment SBχ2 5.143 Df 0≥ 14 Acceptable CFI 0.90≥ acceptable 0.95≥ good fit 0.941 Acceptable PCFI Less than 0.80 0.627 Good fit RMSEA Less than 0.08 0.074 Acceptable RMSEA 95% CI 0.000.08 “good fit” 0.0110.073 Acceptable NFI Greater than 0.90 “good fit” 0.928 Good fit IFI Greater than 0.90 “good fit” 0.941 Good fit PNFI Less than 0.80 0.619 Good fit RMR Less than 0.05 “good fit” 0.036 Acceptable GFI Greater than 0.90 “good fit” 0.958 Not a Good fit “Impact of Monitoring and Evaluation System Factors on Labour Force Management Practices Among Indigenous Construction Firms’ Projects in Ghana.” 8255 ETJ Volume 10 Issue 12 December 2025 , 1 John Yanyi Ampah The unidimensional model for monitoring and evaluation system factors (MESF) features are presented (Figure 8.8 and Table 8.40). Of the twelve (12) indicator variables, seven (7) were obtained and used for the final CFA analysis. (Byrne, 2006: Joreskog and Sorbom, 1988). From the 472 cases analysed for this construct, seven (7) indicator variables made up of a component realised as MESF (MESF1, MESF2, MESF3, MESF4, MES5, MESF7, and MESF10). Table 4: Final Conceptual Model Indicator Variables for Monitoring and Evaluation System Factors (MESF) Latent component Indicator variable Measurement variable Label Monitoring and Evaluation System Factors (MESF) MESF11 Labour participation in the M & E process MESF1 MESF10 Management skills in M & E MESF2 MESF6 Stakeholder involvement in M & E MESF3 MESF8 Organisational guidelines and capacity for M & E MESF4 MESF9 M & E logical framework MESF5 MESF7 Technical capacity and training of the M & E Team MESF7 MESF10 M & E of labour plans implementation MESF10 Figure 1: CFA model for MESF Table 5. presents the values of the correlations, standard errors, and test statistics of the final model with seven indicator variables. All correlation values were less than 1.00, and all pvalues were less than the significance value of 0.05 and were of the right signs. The estimates obtained were thus found to be plausible, in addition to being statistically significant. The standardised coefficient that was the greatest was that of an indicator with variable MESF2, and its parameter coefficient was 0.698. Table 5: Factor Loading and P-Value of MESF Hypothesised relationships (Path) Unstandardised coefficient (λ) Standardised coefficient (λ) PValue R Square Significant at 5% level MESF1  MESF 1.000 0.695 0.00 0.484 Yes MESF2  MESF 1.040 0.698 0.00 0.487 Yes MESF3  MESF 1.046 0.681 0.00 0.464 Yes MESF4  MESF 0.834 0.552 0.00 0.304 Yes MESF5  MESF 0.997 0.654 0.00 0.428 Yes MESF7  MESF 0.903 0.590 0.00 0.348 Yes MESF10  MESF 0.934 0.617 0.00 0.381 Yes Most parameter estimates exhibited high correlation values, nearly reaching 1.00. These elevated correlation values indicate a strong linear relationship between the indicator variables and the unobserved variables related to the MESF. “Impact of Monitoring and Evaluation System Factors on Labour Force Management Practices Among Indigenous Construction Firms’ Projects in Ghana.” 8262 ETJ Volume 10 Issue 12 December 2025 , 1 John Yanyi Ampah 90. Sagharidooz, M., De-Almeida-E-Pais, J. E., Soltanali, H., Farinha, J. T., & Raposo, H. D. N. (2024). Reliability, Availability, and Maintainability Assessment-Based Sustainability-Informed Maintenance Optimization in Power Transmission Networks. Sustainability, 16(15), 6489. https://doi.org/10.3390/su16156489 91. Sajjad, M., Alsulamy, S. H., Waqar, A., Falqi, I. I., Alshehri, A. M., Bageis, A. S., & Hu, A. (2023). Evaluation of the Success of Industry 4.0 Digitalization Practices for Sustainable Construction Management: Chinese Construction Industry. Buildings, 13(7), 1668. https://doi.org/10.3390/buildings13071668 92. Salzano, A., Zitiello, E. P., Nicolella, M., & Cascone, S. (2024). Construction Safety and Efficiency: Integrating Building Information Modeling into Risk Management and Project Execution. Sustainability, 16(10), 4094. https://doi.org/10.3390/su16104094 93. Sohal, A., Bartram, T., Stanton, P., Bamber, G. J., Vasquez, T., & De Vass, T. (2022). Success factors for lean six sigma projects in healthcare. Journal of Management Control, 33(2), 215–240. https://doi.org/10.1007/s00187-022-00336-9 94. Sposito, L., Scafuto, I. C., Serra, F. R., & Ferreira, M. P. (2023). Influence of the project managers’ expertise and experience in the success of projects: the moderating effect of emotional intelligence. International Journal of Managing Projects in Business, 17(1), 1–26. https://doi.org/10.1108/ijmpb06-2023-0129 95. Sreedharan V, R., & Sunder M, V. (2018). A novel approach to lean six sigma project management: a conceptual framework and empirical application. Production Planning & Control, 29(11), 895–907. https://doi.org/10.1080/09537287.2018.1492042 96. Tapera, R., Zetola, N. M., Lord, A., Mhaka-Mutepfa, M., Phaladze, N. A., & Mbongwe, B. (2020). The theory of planned behavior as a behavior change model for tobacco control strategies among adolescents in Botswana. PLOS ONE, 15(6), e0233462. https://doi.org/10.1371/journal.pone.0233462 97. Tasheva, Z., & Karpovich, V. (2024). Supercharge Human Potential Through Ai to Increase Productivity the Workforce in the Companies. American Journal of Applied Science and Technology, 4(2), 24–29. https://doi.org/10.37547/ajast/volume04issue02-05 98. Tengan, C. & Aigbavboa, C. (2016). Evaluating barriers to effective implementation of project monitoring and evaluation in the Ghanaian construction industry. Procedia Engineering, 164, pp. 389–394, doi: 10.1016/j.proeng.2016.11.635. 99. Teasdale, R. M. (2021). Evaluative Criteria: An Integrated Model of Domains and Sources. American Journal of Evaluation, 42(3), 354–376. https://doi.org/10.1177/1098214020955226 100. Tengan, C., & Aigbavboa, C. (2018). Validating factors influencing monitoring and evaluation in the Ghanaian construction industry: a Delphi study approach. International Journal of Construction Management, 21(3), 223–234. https://doi.org/10.1080/15623599.2018.1512353 101. Umar, M., Okwandu, A., & Akande, D. (2024). Impact of effective schedule management on high-rise building projects. International Journal of Applied Research in Social Sciences, 6(7), 1371–1386. https://doi.org/10.51594/ijarss.v6i7.1298 102. Varajão, J., & Trigo, A. (2024). Assessing IT Project Success: Perception vs. Reality. Queue, 22(4), 34–53. https://doi.org/10.1145/3687999 103. Wiefek, J., Nagy, E., & Schäfer, M. (2024). Formative evaluation of transdisciplinary research for systematic impact orientation in real-world laboratories. GAIA - Ecological Perspectives for Science and Society, 33(1), 94–101. https://doi.org/10.14512/gaia.33.s1.14 104. Yadhukrishnan, A.V. & Shetty, A. (2015). A review on GIS-based construction project management. International Advanced Research Journal in Science, Engineering and Technology, 2(6), pp. 137–141. 105. Yu, W.-D., Chang, Y.-H., Ho, W.-C., & Cheng, S.-T. (2018). Measuring the Sustainability of Construction Projects throughout Their Lifecycle: A Taiwan Lesson. Sustainability, 10(5), 1523. https://doi.org/10.3390/su10051523 106. Zangana, H. M., Bazeed, S. M. S., Ali, N. Y., & Abdullah, D. T. (2024). Navigating Project Change: A Comprehensive Review of Change Management Strategies and Practices. Indonesian Journal of Education and Social Sciences, 3(2), 166–179. https://doi.org/10.56916/ijess.v3i2.735