The effect of project management practice on project performance: In the case of Ethiopian Electric Power Gilgel Gibe-III project

The effect of project management practice on project performance: In the case of Ethiopian Electric Power Gilgel Gibe-III project | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article The effect of project management practice on project performance: In the case of Ethiopian Electric Power Gilgel Gibe-III project Tekilew Zewdu Gizaw This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8292106/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract This study examines the impact of project management practices on project performance at the Gibe-III project under Ethiopian Electric Power. A quantitative approach using descriptive and explanatory designs was applied, with data collected from 44 employees. Descriptive statistics revealed neutral responses across seven of eight practice dimensions, with end-of-phase review meetings scoring highest (M = 3.80). Regression analysis showed that 81.8% of performance variation was explained by the identified dimensions (R² = 0.818). Significant predictors included project planning (B = 0.194), implementation (B = 0.138), monitoring and evaluation (B = 0.120), stakeholder engagement (B = 0.113), continuous improvement (B = 0.264), and review meetings (B = 0.278). Procedural documentation and communication were not statistically significant. The study recommends strategic emphasis on planning, implementation, evaluation, continuous improvement, and review mechanisms to enhance project outcomes. Management End-of-phase Review Meetings Project Communication Project Management Project Performance Practices stakeholder involvement 1. Introduction Project management practices (PMP) are the formal application of knowledge, skill, tools, and techniques to project activities to the satisfaction of defined objectives (Project Management Institute [PMI], 2021 ). PMP models like PMBOK, PRINCE2, and Agile frameworks provide standardized processes guiding project managers on how to achieve successful deliverables in different industries (Senapathy, 2023 ). As companies are relying more and more on projects to drive innovation and strategic change, successful implementation of PMP has become a determinant of operational excellence and competitive advantage (PMI, 2021 ). Project performance (PP), on the other hand, focuses on the extent to which a project achieves its planned outcomes under the constraints of time, cost, quality, and stakeholder satisfaction (Burke, 2024). It is usually quantified in terms of key performance indicators (KPIs) like schedule compliance, budget adherence, scope realization, and customer satisfaction. PP is a measurement not just of technical implementation but also of managerial competence, inter-personal relations, and context sensitivity. Merging the last few years' performance domains have redefined the way the success context has been conceptualized or measured concerning a project setting (PMI, 2021 ). The applicability of PMP towards achieving time, cost, and quality goals is highly cited. Effective planning and scheduling practices avoid delays and resource bottlenecking, and sound cost management practices ensure fiscal responsibility and value extraction (Kamau, & Nyang’au, 2021 ); Arabzadeh & Ahmadi-Javid, 2024 ). Quality control methods incorporated within PMP models ensure consistency, conformity, and continuous improvement. Furthermore, stakeholder satisfaction hitherto neglected in traditional models is now recognized as a critical part of PP and has implications on project adoption, legitimacy, and long-term effects (Cheng et al., 2024 ); KnowledgeHut, 2023 ). The complementarity between PMP and PP underscores the need for convergent solutions that reconcile technical rigor with people-centric design. Despite the pervasiveness of PMP models and certifications, many projects continue to underperform or even fail. Evidence shows that poor execution of PMP due to inadequate planning, weak stakeholder management, or inability to accommodate local conditions may lead to cost overruns, late deadlines, and lower quality (PwC, 2014 ). In the developing world, as in Ethiopia, these problems are compounded by resource scarcity, institutional fragmentation, and lack of capacity-building initiatives. This raises serious questions about the contextual relevance of PMP and its actual contribution towards PP in the context of developing project environments. Despite growing emphasis on project-based development in Ethiopia, the majority of projects are still marred with delay, cost overrun, and compromise on quality. A plethora of local studies has attempted to assess project management practice across sectors. For instance, Mulugojjam ( 2020 ) examined problems in monitoring and evaluation in Ethiopian Road Authority projects and found issues of poor stakeholder coordination, inadequate field visits, and inaccurate data. Mersha ( 2023 ) carried out research on federal road project construction and found routine challenges with time, cost, and quality management with weak incorporation of PMBOK standards. Similarly, Gizaw ( 2022 ) assessed the practices of project management by the Ministry of Agriculture, indicating that gaps exist in scope control, communication, and risk management. These studies point out that although PMP frameworks are known, their real application is patchy and contextually downplayed. The research problem analyzed in this study is the mixed relationship between project management practices and project performance within Ethiopian project settings. While PMP models are well promoted, their actual use and ability to cause PP are poorly documented, particularly in public infrastructure, development, and service delivery projects. There is a need to analyze which of the PMP dimensions like planning; monitoring and evaluation, stakeholder communication, and risk management have the biggest effect on PP results within these environments. Therefore, the main objective of this study is to analyze how project management practices affect project performance in Ethiopian Gilgel gibe III project. Specifically, this study aims to: (1) identify the most utilized PMP dimensions; (2) assess the level of project performance through time, cost, quality, and stakeholder satisfaction measures at various times; and (3) examine the statistical relationship between PMP and PP. The research contributes to practice as well as theory by situating PMP within the Ethiopian project context and offering empirical insights into its implications for performance. It bridges the gap between international best practices and domestic contexts, informing policy makers, project managers, and development partners on how to ensure PMP becomes more responsive. In addition, it contributes to the general agenda of capacity building, learning through institutions, and sustainable project management in emerging economies. 2. Literature Review Practice of Project Management (PMP) evolved with internationally accepted frameworks such as PMBOK, PRINCE2, and Agile. The Project Management Institute created the PMBOK Guide that outlines ten knowledge areas and five process groups focusing on integration, scope, time, cost, quality, human resources, communication, risk, procurement, and stakeholder management (Project Management Institute, 2017 ). PMBOK guidelines are commonly referenced in Ethiopia but not uniformly applied, particularly in public infrastructure works (Gebregziabher, 2019 ). PRINCE2 being a process-based method is dependent on business justification, defined roles, and stage-wise control and hence can be tailored to bureaucracy (Vaníčková, 2017 ; Ke et al., 2024 ). Agile having been created to apply to software development, accommodates iterative delivery, engagement with stakeholders, and responsiveness (Raharjo & Purwandari, 2020 ). Despite this, its practice in Ethiopia is hampered by unpreparedness of stakeholders and limited resource (Amanuel, 2022 ). Empirical data across the globe confirm that PMP dimensions of planning, stakeholder management, and monitoring & evaluation are key drivers of project performance (Bergmann & Karwowski, 2018 ; Gracanin, 2019; Liju et al., 2024). In Ethiopia, Gebregziabher ( 2019 ) found inferior PMBOK standards compliance in the UEAP project caused delays and additional costs. Amanuel ( 2022 ) proved poor closure and procurement practices in Plan International Ethiopia projects. Amensisa et al. ( 2024 ) identified quality, procurement, and risk management deficits in the Ethiopian National Stadium project despite successful time and HR practices. Nuredin (2020) referred to poor application of planning tools in Jimma Industrial Park, which affected scope and cost control. Deribe & Endris ( 2022 ) emphasized that monitoring and evaluation specifically stakeholder management and budgeting positively contributed to NGO project success. Theoretical foundations of PMP are grounded in several basic models. Goal-Setting Theory proposes that challenging and specific goals enhance performance (Locke & Latham, 1990). PMP components like review meetings, communication, and structured planning find support from this theory. Systems Theory frames projects as networked subsystems, justifying the need for holistic practices like procedural documentation and stakeholder involvement (Bertalanffy, 1968 ). According to the Resource-Based View (RBV), differentiated and strategically leveraged resources, such as experienced teams and proprietary tools, contribute to enduring performance (Barney, 1991 ). These theories together form a strong lens through which to understand how the PMP dimensions are being quantified into measurable results. There is a conceptual model that relates PMP elements such as project communication, monitoring and evaluation, stakeholder management, capacity planning, procedural documentation, managing multiple projects, continuous improvement, and end-of-phase review meetings to project performance metrics such as cost-effectiveness, time compliance, and quality specifications. These elements are systemically interactive, and the whole implementation affects the sustainability and success of project outcomes (Amensisa et al., 2024 ; Deribe & Endris, 2022 ; Valera-Mendoza, et al., 2024). The inclusion of continuous improvement and multi-project management also bases performance on reproducible and scalable systems (Project Management Institute, 2017 ). 3. Methodology This study adopts a mixed research design of descriptive and explanatory with the aim of investigating comprehensively the effect of project management practices on project performance in Ethiopian Electric Power. Descriptive research is employed to identify existing conditions, stakeholders' attitudes, and procedural characteristics, giving a structured snapshot of project performance indicators such as time, cost, and quality (Creswell, 2009 ). Simultaneously, explanatory research is utilized to test hypotheses and explore causal relationships between specific project management dimensions (e.g., planning, monitoring and evaluation, stakeholder involvement) and performance outcomes. To enhance analysis, a quantitative-methods approach is utilized. Quantitative data were gathered through structured tools for statistically testing relationships between variables (Creswell, 2014 ; Kothari, 2004 ). This methodological triangulation enhances the validity and richness of findings, making possible an in-depth understanding of project dynamics in Ethiopia's infrastructure industry. The population of the study of this research consists of 44 professionals who are directly involved in project execution in Ethiopian Electric Power (EEP), including project managers, engineers, architects, consultants, supervisors, subcontractor representatives, and supporting staff who take part in planning, architecture, supply chain, and management tasks. Because of the technicality of the research, a judgmental sampling technique a form of non-probability sampling was employed to purposively sample participants with targeted expertise and experience (Creswell, 2009 ). Since the population is manageable and small, the researcher used the census approach, including all 44 subjects to have full coverage and minimize sampling error (Kothari, 2004 ). This approach enhances the validity of findings without utilizing excessive resources on large-scale sampling. The study utilized primary data sources for the full scope of the research objectives. The primary data were collected with the help of structured questionnaires, and the questionnaire was the principal instrument. It was derived based on project management theory and empirical studies, consisting of close-ended questions on a five-point Likert scale to collect demographic data and project data. This design provides ease of response and enables quantitative data to be obtained from professionals and project managers. The data analysis was conducted using SPSS version 26, utilizing descriptive statistics (mean, and standard deviation) and inferential techniques comprising correlation and regression analysis in examining relationships between project management practices and performance. To ensure reliability, Cronbach's alphas were utilized to compute internal consistency, with acceptable ranges prescribed between 0.6 and 0.7 for reasonable reliability (Zikmund et al., 2010), and above 0.7 as ideal (Pallant, 2005 ). 4. Result and Discussion Table 1: Project management practices and project performance The composite mean scores would reveal that neutral attitudes dominate seven project management dimensions measured. All the major areas have returned ranges in the middle, indicating neither support nor opposition relating to their effectiveness and impact concerning project planning (2.75), implementation (2.83), monitoring and evaluation (2.82), communication (2.92), stakeholder engagement (3.27), and procedural documentation (2.94). Such neutrality suggests that while these components are present in organizational practice, they are not being built to strategic depth or deployed frequently enough to yield strong, positive beliefs about their impact on performance. The lowest rating, continuous improvement (2.58), suggests a potential weakness in adaptive learning and process refinement two processes central to iterative success in project environments in transition. 4.1 Relationship between Project Management practices with project Performance Identification of the level of association of the selected independent variables (project planning, project execution, project monitoring and evaluation, project communication, involvement of stakeholders, development of effective procedural documentation, Continuous improvement, end of end of phase review meetings) with project performance is the main aim of carrying out an analysis with the help of Pearson correlation. Table 2: Relationship between Project Management practices with project Performance The results from the analysis show that a number of project management's central dimensions are highly and significantly related to project performance. Of those, implementation in projects has the highest positive correlation (.779, p < .001), i.e., good practice of execution is critical success drivers. Similarly, continuous improvement (r = .723, p < .001), project planning (r = .651, p < .001), and project communication (r = .666, p < .001) also have high correlations, which mean that systematic planning and active communication, as well as ongoing learning, are crucial elements in ensuring project results. The significance is at moderate levels for monitoring and evaluation, r = .592, p < .001 and end-of-phase review meetings, r = .397, p = .009, which indicates the necessity of accountability and systematic reflection for better performance. Conversely, the results indicate that stakeholder involvement (r = .249, p = .112) and producing effective procedural documents (r = .189, p = .231) are unrelated to project performance in the case of this sample. The results may reflect situational challenges in stakeholder involvement or procedural standardization limitations within the project environment of Ethiopian Electric Power. Such findings indicate that although internal working practices significantly affect performance, more importance can be placed on inclusive governance and systematic documentation to support long-term project sustainability and external credibility. 4.1 Effect of Project Management practices on project Performance Regression analysis is a methodology whose application can be used in the context of analyzing how one or more predictor variables affect dependent variable. That is, it allows one to make statements regarding the capability of one or more independent variables to forecast the value of a dependent variable. Specifically, this multiple regression was conducted in an attempt to analyze the effect entire bundle of selected determinant factors has on project performance. The set of project management practices has statistically significant and positive correlation with performance of Ethiopian Electric power Gibe-III project. Table 3: Multiple regression result We can see from the above table regression analysis provides a good fit to the model with R .904 and R² .818, which establishes that approximately 81.8% of the variation in project performance is explained by the set of eight predictor variables. The .774 adjusted R² also confirms the power of the model by adjusting for the number of predictors versus sample size, meaning the model is explanatory and parsimonious. The overall highly significant model is indicated by the F-statistic (F = 18.540, p < .001), which means independent variables collectively have a significant predictive effect on project performance. The .17867 standard error of estimate shows relatively low prediction error, and the Durbin-Watson statistic (1.792) is between good limits, showing no serious autocorrelation of the residuals. These results affirm that project planning and implementation, communications, monitoring and evaluation, and continuous improvement are key drivers of performance outcomes in the case of the Ethiopian Electric Power. Table 4: Anova result The ANOVA test confirms that the regression model is statistically significant in predicting project performance, as evidenced by an F-statistic of 18.540 and a p-value of .000 (p < .001). This shows that the variation explained by the eight predictor variables such as project planning, implementation, communication, monitoring, stakeholder involvement, and continuous improvement is far greater than the unexplained variation in the data. Sum of squares in regression (SS = 4.735), compared to residual sum of squares (SS = 1.053), highlights that the majority of variability in project performance is explained by the model, with comparatively minimal remainder accounted for by error. The model thus consistently distinguishes significant differences and relationships, validating the overall contribution of the predictors to performance outcomes for the Ethiopian Electric Power example. Table 5: Multiple regression Coefficients result The regression coefficients show that certain independent variables statistically significantly influence the performance of projects, most notably end-of-phase review meetings (β = .407, p = .001) and continuous improvement (β = .322, p = .007), both with significant standardized effects and large t-values. These implications show that practices improving iterative learning as well as systematic feedback are most success-driving in the Ethiopian Electric Power model of project management. Similarly, project implementation (β = .279, p < .001), project planning (β = .257, p = .029), monitoring and evaluation (β = .236, p = .016), and stakeholders' involvement (β = .247, p = .038) are positively correlated with performance, which serves to justify their roles in the alignment of strategic implementation with intended goals. Of special interest is that stakeholder participation appears more influential in regression than in simple correlation, implying its impact may be greater when taken together with other variables. In contrast, project communication (β = .063, p = .615) and procedure documentation (β = .014, p = .871) do not significantly influence anything, implying that neither contributes any significant value to performance outcomes here. This may be a sign of operational issues such as limited feedback channels, excessive standardization, or insufficient document integration into decision-making. While these elements are typically accorded immense significance within project settings, the limited role they have to play in this model suggests a need to reconsider or complement the processes by which communication and documentation are harnessed. Generally, the model lays immense emphasis on executional discipline, stakeholder alignment, and adaptive learning as the practices having the greatest impact on performance success. Table 6: Summary of hypothesis result 4.2 Discussions The study's regression findings are in line with a growing body of literature emphasizing the strategic significance of integrated project management practices as prime drivers of performance outcomes. As an example, the crucial contribution of end-of-phase review meetings and continuous improvement is reinforcing propositions from Shah, Bhatti, and Ahmed (2023), which posit that formal feedback loops and multiple learning impacts significantly enhance project delivery and stakeholder satisfaction. In the same vein, Adegbite et al. (2023) point out that adaptive planning and reflective review systems are necessary in managing intricate project landscapes, particularly in developing economies. These works further substantiate the idea that performance is not only a matter of execution but also of how effectively organizations institutionalize learning as well as accountability during the project life cycle. Furthermore, the model's key impacts of planning, executing, and monitoring and evaluating the project is consistent with recent empirical research around the world. Ibrahim, et al., (2024) developed a Project Performance Index that integrates planning and risk management as key determinants of success, whereas Ullah, et al., (2024) found competency-driven planning and execution models specifically IPMA-based models yield higher sustainability and cost-effectiveness. In Ethiopia, Gizaw (2022) and Amensisa et al. (2024) also discovered structured monitoring and planning practices as being vital to improving performance for public infrastructure projects. The implications of these findings are that technical sophistication, when combined with contextual sensitivity, realizes measurable gains in time, cost, and quality performances. On the other hand, the relatively weak contribution of project communication and procedural documentation in the regression equation suggests a subtlety of challenge also reported in the literature. Whereas PMI (2021) and Stanleigh (2011) encourage standardized communication and documentation as foundations for consistency, studies by Cork (2015) and Solomon Gizaw (2022) discover that in the field, these elements are often not implemented or even viewed as compliance artifacts, rather than strategic assets. That distinction may be the reason for their weak statistical contribution despite theoretical relevance. It stresses that the use of best practices by organizations must be accompanied by embedding them effectively into team structures and decision-making. 5. Conclusion Based on the regression analysis and results, the study concludes that project performance is significantly shaped by a blend of strategic and operational management practices. Among the key drivers, end-of-phase review meetings, continuous improvement efforts, structured planning, and robust monitoring and evaluation systems emerged as the most impactful predictors. These components not only enhance execution efficiency but also promote adaptive learning and accountability within the project lifecycle. The findings affirm that project success is a function of proactive design, critical oversight, and institutionalized review mechanisms that transform procedural rigor into tangible performance gains. However, the relatively limited influence of project communication and procedural documentation suggests that technical inputs alone are insufficient unless integrated meaningfully into project culture and decision-making processes. This highlights a subtle gap between theoretical frameworks and actual organizational behavior. As a result, future implementation strategies should not only emphasize planning and monitoring but also reconfigure softer elements like communication to ensure they contribute effectively to performance outcomes. In sum, the study offers an evidence-based foundation for enhancing project management practices through targeted, context-responsive interventions, particularly in emerging professional environments. 5.1 Suggestions for Future Work Finally it is recommended that Exploring how organizational culture and team dynamics mediate project management outcomes can uncover critical behavioral and structural factors that enhance or hinder success. Additionally, conducting sector-specific analyses allows for tailoring project performance frameworks to the unique operational realities and stakeholder expectations of different industries, ensuring relevance and impact. Declarations Acknowledgements Not applicable. Authors’ contributions The author of this article is Tekilew Zewdu Gizaw and the author read and approved the final manuscript. Funding There is no any funding information for this research. Availability of data and materials All data generated or analyzed during this study are available from the author upon reasonable request. Ethics approval and consent to participate Ethics Approval Statement: This study was approved by the Addis Ababa University College of Business and Economics, School of Commerce Research Ethics Committee. All participants provided informed consent prior to data collection. Consent for publication The entire participant has consented to the submission of the paper to the journal for publication. 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International Journal of Communication Networks and Information Security, 16 (4), 1088–1101. https://doi.org/10.15849/ijcnis.v16i4.7310 Tables Table 1: Project management practices and project performance No Independent Variable Aggregate Mean Interpretation 1 Project Planning 2.75 Neutral 2 Project Implementation 2.83 Neutral 3 Project Monitoring and Evaluation 2.82 Neutral 4 Project Communication 2.92 Neutral 5 Stakeholder Involvement 3.27 Neutral 6 developing effective procedural documentation 2.94 Neutral 7 Continuous Improvement 2.58 Neutral 8 End-of-phase review meetings 3.80 Agree 9 Project Performance 2.75 Neutral Table 2: Relationship between Project Management practices with project Performance Project Performance Project Planning Pearson Correlation .651 ** Sig. (2-tailed) .000 N 42 Project implementation Pearson Correlation .779 ** Sig. (2-tailed) .000 N 42 Project Monitoring and evaluation Pearson Correlation .592 ** Sig. (2-tailed) .000 N 42 Project Communication Pearson Correlation .666 ** Sig. (2-tailed) .000 N 42 Stakeholder Involvement Pearson Correlation .249 Sig. (2-tailed) .112 N 42 Developing Effective Procedural Documentation Pearson Correlation .189 Sig. (2-tailed) .231 N 42 Continuous Improvement Pearson Correlation .723 ** Sig. (2-tailed) .000 N 42 End of Phase Review Meetings Pearson Correlation .397 ** Sig. (2-tailed) .009 N 42 Project Performance Pearson Correlation 1 Sig. (2-tailed) N 42 Table 3: Multiple regression result Model Summary b Model R R Square Adjusted R Square Std. Error of the Estimate Change Statistics Durbin-Watson R Square Change F Change df1 df2 Sig. F Change 1 .904 a .818 .774 .17867 .818 18.540 8 33 .000 1.792 a. Predictors: (Constant), End of Phase Review Meetings, Developing Effective Procedural Documentation, Project Monitoring and evaluation, Project Planning, Continuous Improvement, Stakeholder Involvement, Project Communication, Project implementation b. Dependent Variable: Project Performance Table 4: Anova result ANOVA a Model Sum of Squares Df Mean Square F Sig. 1 Regression 4.735 8 .592 18.540 .000 b Residual 1.053 33 .032 Total 5.788 41 a. Dependent Variable: Project Performance b. Predictors: (Constant), End of Phase Review Meetings, Developing Effective Procedural Documentation, Project Monitoring and evaluation, Project Planning, Continuous Improvement, Stakeholder Involvement, Project Communication, Project implementation Table 5: Multiple regression Coefficients result Model Unstandardized Coefficients Standardized Coefficients T Sig. B Std. Error Beta 1 (Constant) .219 .308 .710 .482 Project Planning .194 .085 .257 2.277 .029 Project implementation .138 .074 .279 2.875 .000 Project Monitoring and evaluation .120 .047 .236 2.528 .016 Project Communication .037 .072 .063 .508 .615 Stakeholder Involvement .113 .052 .247 2.161 .038 Developing Effective Procedural Documentation .008 .047 .014 .164 .871 Continuous Improvement .264 .092 .322 2.869 .007 End of Phase Review Meetings .278 .074 .407 3.734 .001 Table 6: Summary of hypothesis result No Hypothesis Result Decision 1 H1: Project Planning has a positive relationship and statistically significant effect on the project performance. r=0.779/p=0.000 B=0.138/ p<0.01 Accepted 2 H2: Project implementation has a positive relationship and statistically significant effect on project performance r=0.779/p=0.000 B=0.138/ p<0.01 Accepted 3 H3: Project Monitoring and evaluation has a positive relationship and statistically significant effect on project performance r=0.592/p=0.000 B=0.120/ p0.05 Not accepted 5 H5: Stakeholder involvement has a positive relationship and statistically significant effect on project performance. r=0.249/ p=0.112 B=0.113/ p0.05 Not accepted 7 H7: Continuous improvement has a positive relationship and statistically significant effect on project performance r=0.723/p= 0.000 B=0.264/ p<0.01 Accepted 8 H8: End-of-phase review meetings have a positive relationship and statistically significant effect on project performance r=0.397/p= 0.009 B=0.278/ p<0.01 Accepted Additional Declarations The authors declare no competing interests. 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Introduction","content":"\u003cp\u003eProject management practices (PMP) are the formal application of knowledge, skill, tools, and techniques to project activities to the satisfaction of defined objectives (Project Management Institute [PMI], \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). PMP models like PMBOK, PRINCE2, and Agile frameworks provide standardized processes guiding project managers on how to achieve successful deliverables in different industries (Senapathy, \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). As companies are relying more and more on projects to drive innovation and strategic change, successful implementation of PMP has become a determinant of operational excellence and competitive advantage (PMI, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eProject performance (PP), on the other hand, focuses on the extent to which a project achieves its planned outcomes under the constraints of time, cost, quality, and stakeholder satisfaction (Burke, 2024). It is usually quantified in terms of key performance indicators (KPIs) like schedule compliance, budget adherence, scope realization, and customer satisfaction. PP is a measurement not just of technical implementation but also of managerial competence, inter-personal relations, and context sensitivity. Merging the last few years' performance domains have redefined the way the success context has been conceptualized or measured concerning a project setting (PMI, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe applicability of PMP towards achieving time, cost, and quality goals is highly cited. Effective planning and scheduling practices avoid delays and resource bottlenecking, and sound cost management practices ensure fiscal responsibility and value extraction (Kamau, \u0026amp; Nyang\u0026rsquo;au, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2021\u003c/span\u003e); Arabzadeh \u0026amp; Ahmadi-Javid, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Quality control methods incorporated within PMP models ensure consistency, conformity, and continuous improvement. Furthermore, stakeholder satisfaction hitherto neglected in traditional models is now recognized as a critical part of PP and has implications on project adoption, legitimacy, and long-term effects (Cheng et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2024\u003c/span\u003e); KnowledgeHut, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). The complementarity between PMP and PP underscores the need for convergent solutions that reconcile technical rigor with people-centric design.\u003c/p\u003e\u003cp\u003eDespite the pervasiveness of PMP models and certifications, many projects continue to underperform or even fail. Evidence shows that poor execution of PMP due to inadequate planning, weak stakeholder management, or inability to accommodate local conditions may lead to cost overruns, late deadlines, and lower quality (PwC, \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). In the developing world, as in Ethiopia, these problems are compounded by resource scarcity, institutional fragmentation, and lack of capacity-building initiatives. This raises serious questions about the contextual relevance of PMP and its actual contribution towards PP in the context of developing project environments.\u003c/p\u003e\u003cp\u003eDespite growing emphasis on project-based development in Ethiopia, the majority of projects are still marred with delay, cost overrun, and compromise on quality. A plethora of local studies has attempted to assess project management practice across sectors. For instance, Mulugojjam (\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) examined problems in monitoring and evaluation in Ethiopian Road Authority projects and found issues of poor stakeholder coordination, inadequate field visits, and inaccurate data. Mersha (\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) carried out research on federal road project construction and found routine challenges with time, cost, and quality management with weak incorporation of PMBOK standards. Similarly, Gizaw (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) assessed the practices of project management by the Ministry of Agriculture, indicating that gaps exist in scope control, communication, and risk management. These studies point out that although PMP frameworks are known, their real application is patchy and contextually downplayed.\u003c/p\u003e\u003cp\u003eThe research problem analyzed in this study is the mixed relationship between project management practices and project performance within Ethiopian project settings. While PMP models are well promoted, their actual use and ability to cause PP are poorly documented, particularly in public infrastructure, development, and service delivery projects. There is a need to analyze which of the PMP dimensions like planning; monitoring and evaluation, stakeholder communication, and risk management have the biggest effect on PP results within these environments.\u003c/p\u003e\u003cp\u003eTherefore, the main objective of this study is to analyze how project management practices affect project performance in Ethiopian Gilgel gibe III project. Specifically, this study aims to: (1) identify the most utilized PMP dimensions; (2) assess the level of project performance through time, cost, quality, and stakeholder satisfaction measures at various times; and (3) examine the statistical relationship between PMP and PP.\u003c/p\u003e\u003cp\u003eThe research contributes to practice as well as theory by situating PMP within the Ethiopian project context and offering empirical insights into its implications for performance. It bridges the gap between international best practices and domestic contexts, informing policy makers, project managers, and development partners on how to ensure PMP becomes more responsive. In addition, it contributes to the general agenda of capacity building, learning through institutions, and sustainable project management in emerging economies.\u003c/p\u003e"},{"header":"2. Literature Review","content":"\u003cp\u003ePractice of Project Management (PMP) evolved with internationally accepted frameworks such as PMBOK, PRINCE2, and Agile. The Project Management Institute created the PMBOK Guide that outlines ten knowledge areas and five process groups focusing on integration, scope, time, cost, quality, human resources, communication, risk, procurement, and stakeholder management (Project Management Institute, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). PMBOK guidelines are commonly referenced in Ethiopia but not uniformly applied, particularly in public infrastructure works (Gebregziabher, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). PRINCE2 being a process-based method is dependent on business justification, defined roles, and stage-wise control and hence can be tailored to bureaucracy (Van\u0026iacute;čkov\u0026aacute;, \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Ke et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Agile having been created to apply to software development, accommodates iterative delivery, engagement with stakeholders, and responsiveness (Raharjo \u0026amp; Purwandari, \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Despite this, its practice in Ethiopia is hampered by unpreparedness of stakeholders and limited resource (Amanuel, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eEmpirical data across the globe confirm that PMP dimensions of planning, stakeholder management, and monitoring \u0026amp; evaluation are key drivers of project performance (Bergmann \u0026amp; Karwowski, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Gracanin, 2019; Liju et al., 2024). In Ethiopia, Gebregziabher (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) found inferior PMBOK standards compliance in the UEAP project caused delays and additional costs. Amanuel (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) proved poor closure and procurement practices in Plan International Ethiopia projects. Amensisa et al. (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) identified quality, procurement, and risk management deficits in the Ethiopian National Stadium project despite successful time and HR practices. Nuredin (2020) referred to poor application of planning tools in Jimma Industrial Park, which affected scope and cost control. Deribe \u0026amp; Endris (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) emphasized that monitoring and evaluation specifically stakeholder management and budgeting positively contributed to NGO project success.\u003c/p\u003e\u003cp\u003eTheoretical foundations of PMP are grounded in several basic models. Goal-Setting Theory proposes that challenging and specific goals enhance performance (Locke \u0026amp; Latham, 1990). PMP components like review meetings, communication, and structured planning find support from this theory. Systems Theory frames projects as networked subsystems, justifying the need for holistic practices like procedural documentation and stakeholder involvement (Bertalanffy, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e1968\u003c/span\u003e). According to the Resource-Based View (RBV), differentiated and strategically leveraged resources, such as experienced teams and proprietary tools, contribute to enduring performance (Barney, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e1991\u003c/span\u003e). These theories together form a strong lens through which to understand how the PMP dimensions are being quantified into measurable results.\u003c/p\u003e\u003cp\u003eThere is a conceptual model that relates PMP elements such as project communication, monitoring and evaluation, stakeholder management, capacity planning, procedural documentation, managing multiple projects, continuous improvement, and end-of-phase review meetings to project performance metrics such as cost-effectiveness, time compliance, and quality specifications. These elements are systemically interactive, and the whole implementation affects the sustainability and success of project outcomes (Amensisa et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Deribe \u0026amp; Endris, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Valera-Mendoza, et al., 2024). The inclusion of continuous improvement and multi-project management also bases performance on reproducible and scalable systems (Project Management Institute, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e"},{"header":"3. Methodology","content":"\u003cp\u003eThis study adopts a mixed research design of descriptive and explanatory with the aim of investigating comprehensively the effect of project management practices on project performance in Ethiopian Electric Power. Descriptive research is employed to identify existing conditions, stakeholders' attitudes, and procedural characteristics, giving a structured snapshot of project performance indicators such as time, cost, and quality (Creswell, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). Simultaneously, explanatory research is utilized to test hypotheses and explore causal relationships between specific project management dimensions (e.g., planning, monitoring and evaluation, stakeholder involvement) and performance outcomes. To enhance analysis, a quantitative-methods approach is utilized. Quantitative data were gathered through structured tools for statistically testing relationships between variables (Creswell, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Kothari, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2004\u003c/span\u003e). This methodological triangulation enhances the validity and richness of findings, making possible an in-depth understanding of project dynamics in Ethiopia's infrastructure industry.\u003c/p\u003e\u003cp\u003eThe population of the study of this research consists of 44 professionals who are directly involved in project execution in Ethiopian Electric Power (EEP), including project managers, engineers, architects, consultants, supervisors, subcontractor representatives, and supporting staff who take part in planning, architecture, supply chain, and management tasks. Because of the technicality of the research, a judgmental sampling technique a form of non-probability sampling was employed to purposively sample participants with targeted expertise and experience (Creswell, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). Since the population is manageable and small, the researcher used the census approach, including all 44 subjects to have full coverage and minimize sampling error (Kothari, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2004\u003c/span\u003e). This approach enhances the validity of findings without utilizing excessive resources on large-scale sampling.\u003c/p\u003e\u003cp\u003eThe study utilized primary data sources for the full scope of the research objectives. The primary data were collected with the help of structured questionnaires, and the questionnaire was the principal instrument. It was derived based on project management theory and empirical studies, consisting of close-ended questions on a five-point Likert scale to collect demographic data and project data. This design provides ease of response and enables quantitative data to be obtained from professionals and project managers. The data analysis was conducted using SPSS version 26, utilizing descriptive statistics (mean, and standard deviation) and inferential techniques comprising correlation and regression analysis in examining relationships between project management practices and performance. To ensure reliability, Cronbach's alphas were utilized to compute internal consistency, with acceptable ranges prescribed between 0.6 and 0.7 for reasonable reliability (Zikmund et al., 2010), and above 0.7 as ideal (Pallant, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2005\u003c/span\u003e).\u003c/p\u003e"},{"header":"4. Result and Discussion","content":"\u003cp\u003eTable 1: Project management practices and project performance\u003c/p\u003e\n\u003cp\u003eThe composite mean scores would reveal that neutral attitudes dominate seven project management dimensions measured. All the major areas have returned ranges in the middle, indicating neither support nor opposition relating to their effectiveness and impact concerning project planning (2.75), implementation (2.83), monitoring and evaluation (2.82), communication (2.92), stakeholder engagement (3.27), and procedural documentation (2.94). Such neutrality suggests that while these components are present in organizational practice, they are not being built to strategic depth or deployed frequently enough to yield strong, positive beliefs about their impact on performance. The lowest rating, continuous improvement (2.58), suggests a potential weakness in adaptive learning and process refinement two processes central to iterative success in project environments in transition.\u003c/p\u003e\n\u003ch2\u003e\u003cstrong\u003e4.1 Relationship between Project Management practices with project Performance\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eIdentification of the level of association of the selected independent variables (project planning, project execution, project monitoring and evaluation, project communication, involvement of stakeholders, development of effective procedural documentation, Continuous improvement, end of end of phase review meetings) with project performance is the main aim of carrying out an analysis with the help of Pearson correlation.\u003c/p\u003e\n\u003cp\u003eTable 2: Relationship between Project Management practices with project Performance\u003c/p\u003e\n\u003cp\u003eThe results from the analysis show that a number of project management\u0026apos;s central dimensions are highly and significantly related to project performance. Of those, implementation in projects has the highest positive correlation (.779, p \u0026lt; .001), i.e., good practice of execution is critical success drivers. Similarly, continuous improvement (r = .723, p \u0026lt; .001), project planning (r = .651, p \u0026lt; .001), and project communication (r = .666, p \u0026lt; .001) also have high correlations, which mean that systematic planning and active communication, as well as ongoing learning, are crucial elements in ensuring project results. The significance is at moderate levels for monitoring and evaluation, r = .592, p \u0026lt; .001 and end-of-phase review meetings, r = .397, p = .009, which indicates the necessity of accountability and systematic reflection for better performance.\u003c/p\u003e\n\u003cp\u003eConversely, the results indicate that stakeholder involvement (r = .249, p = .112) and producing effective procedural documents (r = .189, p = .231) are unrelated to project performance in the case of this sample. The results may reflect situational challenges in stakeholder involvement or procedural standardization limitations within the project environment of Ethiopian Electric Power. Such findings indicate that although internal working practices significantly affect performance, more importance can be placed on inclusive governance and systematic documentation to support long-term project sustainability and external credibility.\u003c/p\u003e\n\u003ch2\u003e\u003cstrong\u003e4.1 Effect of Project Management practices on project Performance\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eRegression analysis is a methodology whose application can be used in the context of analyzing how one or more predictor variables affect dependent variable. That is, it allows one to make statements regarding the capability of one or more independent variables to forecast the value of a dependent variable. Specifically, this multiple regression was conducted in an attempt to analyze the effect entire bundle of selected determinant factors has on project performance. The set of project management practices has statistically significant and positive correlation with performance of Ethiopian Electric power Gibe-III project.\u003c/p\u003e\n\u003cp\u003eTable 3: Multiple regression result\u003c/p\u003e\n\u003cp\u003eWe can see from the above table regression analysis provides a good fit to the model with R .904 and R\u0026sup2; .818, which establishes that approximately 81.8% of the variation in project performance is explained by the set of eight predictor variables. The .774 adjusted R\u0026sup2; also confirms the power of the model by adjusting for the number of predictors versus sample size, meaning the model is explanatory and parsimonious. The overall highly significant model is indicated by the F-statistic (F = 18.540, p \u0026lt; .001), which means independent variables collectively have a significant predictive effect on project performance. The .17867 standard error of estimate shows relatively low prediction error, and the Durbin-Watson statistic (1.792) is between good limits, showing no serious autocorrelation of the residuals. These results affirm that project planning and implementation, communications, monitoring and evaluation, and continuous improvement are key drivers of performance outcomes in the case of the Ethiopian Electric Power.\u003c/p\u003e\n\u003cp\u003eTable 4: Anova result\u003c/p\u003e\n\u003cp\u003eThe ANOVA test confirms that the regression model is statistically significant in predicting project performance, as evidenced by an F-statistic of 18.540 and a p-value of .000 (p \u0026lt; .001). This shows that the variation explained by the eight predictor variables such as project planning, implementation, communication, monitoring, stakeholder involvement, and continuous improvement is far greater than the unexplained variation in the data. Sum of squares in regression (SS = 4.735), compared to residual sum of squares (SS = 1.053), highlights that the majority of variability in project performance is explained by the model, with comparatively minimal remainder accounted for by error. The model thus consistently distinguishes significant differences and relationships, validating the overall contribution of the predictors to performance outcomes for the Ethiopian Electric Power example.\u003c/p\u003e\n\u003cp\u003eTable 5: Multiple regression Coefficients result\u003c/p\u003e\n\u003cp\u003eThe regression coefficients show that certain independent variables statistically significantly influence the performance of projects, most notably end-of-phase review meetings (\u0026beta; = .407, p = .001) and continuous improvement (\u0026beta; = .322, p = .007), both with significant standardized effects and large t-values. These implications show that practices improving iterative learning as well as systematic feedback are most success-driving in the Ethiopian Electric Power model of project management. Similarly, project implementation (\u0026beta; = .279, p \u0026lt; .001), project planning (\u0026beta; = .257, p = .029), monitoring and evaluation (\u0026beta; = .236, p = .016), and stakeholders\u0026apos; involvement (\u0026beta; = .247, p = .038) are positively correlated with performance, which serves to justify their roles in the alignment of strategic implementation with intended goals. Of special interest is that stakeholder participation appears more influential in regression than in simple correlation, implying its impact may be greater when taken together with other variables.\u003c/p\u003e\n\u003cp\u003eIn contrast, project communication (\u0026beta; = .063, p = .615) and procedure documentation (\u0026beta; = .014, p = .871) do not significantly influence anything, implying that neither contributes any significant value to performance outcomes here. This may be a sign of operational issues such as limited feedback channels, excessive standardization, or insufficient document integration into decision-making. While these elements are typically accorded immense significance within project settings, the limited role they have to play in this model suggests a need to reconsider or complement the processes by which communication and documentation are harnessed. Generally, the model lays immense emphasis on executional discipline, stakeholder alignment, and adaptive learning as the practices having the greatest impact on performance success.\u003c/p\u003e\n\u003cp\u003eTable 6: Summary of hypothesis result\u003c/p\u003e\n\u003ch2\u003e4.2 Discussions\u003c/h2\u003e\n\u003cp\u003eThe study\u0026apos;s regression findings are in line with a growing body of literature emphasizing the strategic significance of integrated project management practices as prime drivers of performance outcomes. As an example, the crucial contribution of end-of-phase review meetings and continuous improvement is reinforcing propositions from Shah, Bhatti, and Ahmed (2023), which posit that formal feedback loops and multiple learning impacts significantly enhance project delivery and stakeholder satisfaction. In the same vein, Adegbite et al. (2023) point out that adaptive planning and reflective review systems are necessary in managing intricate project landscapes, particularly in developing economies. These works further substantiate the idea that performance is not only a matter of execution but also of how effectively organizations institutionalize learning as well as accountability during the project life cycle.\u003c/p\u003e\n\u003cp\u003eFurthermore, the model\u0026apos;s key impacts of planning, executing, and monitoring and evaluating the project is consistent with recent empirical research around the world. Ibrahim, et al., (2024) developed a Project Performance Index that integrates planning and risk management as key determinants of success, whereas Ullah, et al., (2024) found competency-driven planning and execution models specifically IPMA-based models yield higher sustainability and cost-effectiveness. In Ethiopia, Gizaw (2022) and Amensisa et al. (2024) also discovered structured monitoring and planning practices as being vital to improving performance for public infrastructure projects. The implications of these findings are that technical sophistication, when combined with contextual sensitivity, realizes measurable gains in time, cost, and quality performances.\u003c/p\u003e\n\u003cp\u003eOn the other hand, the relatively weak contribution of project communication and procedural documentation in the regression equation suggests a subtlety of challenge also reported in the literature. Whereas PMI (2021) and Stanleigh (2011) encourage standardized communication and documentation as foundations for consistency, studies by Cork (2015) and Solomon Gizaw (2022) discover that in the field, these elements are often not implemented or even viewed as compliance artifacts, rather than strategic assets. That distinction may be the reason for their weak statistical contribution despite theoretical relevance. It stresses that the use of best practices by organizations must be accompanied by embedding them effectively into team structures and decision-making.\u003c/p\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003eBased on the regression analysis and results, the study concludes that project performance is significantly shaped by a blend of strategic and operational management practices. Among the key drivers, end-of-phase review meetings, continuous improvement efforts, structured planning, and robust monitoring and evaluation systems emerged as the most impactful predictors. These components not only enhance execution efficiency but also promote adaptive learning and accountability within the project lifecycle. The findings affirm that project success is a function of proactive design, critical oversight, and institutionalized review mechanisms that transform procedural rigor into tangible performance gains.\u003c/p\u003e\n\u003cp\u003eHowever, the relatively limited influence of project communication and procedural documentation suggests that technical inputs alone are insufficient unless integrated meaningfully into project culture and decision-making processes. This highlights a subtle gap between theoretical frameworks and actual organizational behavior. As a result, future implementation strategies should not only emphasize planning and monitoring but also reconfigure softer elements like communication to ensure they contribute effectively to performance outcomes. In sum, the study offers an evidence-based foundation for enhancing project management practices through targeted, context-responsive interventions, particularly in emerging professional environments.\u003c/p\u003e\n\u003ch2\u003e5.1 Suggestions for Future Work\u003c/h2\u003e\n\u003cp\u003eFinally it is recommended that Exploring how organizational culture and team dynamics mediate project management outcomes can uncover critical behavioral and structural factors that enhance or hinder success. Additionally, conducting sector-specific analyses allows for tailoring project performance frameworks to the unique operational realities and stakeholder expectations of different industries, ensuring relevance and impact.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe author of this article is Tekilew Zewdu Gizaw and the author read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThere is no any funding information for this research.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll data generated or analyzed during this study are available from the author upon reasonable request.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics Approval Statement:\u003c/strong\u003e This study was approved by the Addis Ababa University College of Business and Economics, School of Commerce Research Ethics Committee. All participants provided informed consent prior to data collection.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe entire participant has consented to the submission of the paper to the journal for publication.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe author has no competing interests to declare that are relevant to the content of this article.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAdegbite, A. O., Adefemi, A., Ukpoju, E. A., Abatan, A., Adekoya, O., \u0026amp; Obaedo, B. O. (2023). \u003cem\u003eInnovations in project management: Trends and best practices\u003c/em\u003e. Engineering Science \u0026amp; Technology Journal, 4(6), 509\u0026ndash;532.\u003c/li\u003e\n\u003cli\u003eAmensisa, A., et al. 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Intelligent systems for project management in public institutions: A review of the state of the art in Scopus. \u003cem\u003eInternational Journal of Communication Networks and Information Security, 16\u003c/em\u003e(4), 1088\u0026ndash;1101. https://doi.org/10.15849/ijcnis.v16i4.7310\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTable 1: Project management practices and project performance\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 7.69231%;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 51.9231%;\"\u003e\n \u003cp\u003eIndependent Variable\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.2692%;\"\u003e\n \u003cp\u003eAggregate Mean\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.1154%;\"\u003e\n \u003cp\u003eInterpretation\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 7.69231%;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 51.9231%;\"\u003e\n \u003cp\u003eProject Planning\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.2692%;\"\u003e\n \u003cp\u003e2.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.1154%;\"\u003e\n \u003cp\u003eNeutral\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 7.69231%;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 51.9231%;\"\u003e\n \u003cp\u003eProject Implementation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.2692%;\"\u003e\n \u003cp\u003e2.83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.1154%;\"\u003e\n \u003cp\u003eNeutral\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 7.69231%;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 51.9231%;\"\u003e\n \u003cp\u003eProject Monitoring and Evaluation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.2692%;\"\u003e\n \u003cp\u003e2.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.1154%;\"\u003e\n \u003cp\u003eNeutral\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 7.69231%;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 51.9231%;\"\u003e\n \u003cp\u003eProject Communication\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.2692%;\"\u003e\n \u003cp\u003e2.92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.1154%;\"\u003e\n \u003cp\u003eNeutral\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 7.69231%;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 51.9231%;\"\u003e\n \u003cp\u003eStakeholder Involvement\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.2692%;\"\u003e\n \u003cp\u003e3.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.1154%;\"\u003e\n \u003cp\u003eNeutral\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 7.69231%;\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 51.9231%;\"\u003e\n \u003cp\u003edeveloping effective procedural documentation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.2692%;\"\u003e\n \u003cp\u003e2.94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.1154%;\"\u003e\n \u003cp\u003eNeutral\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 7.69231%;\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 51.9231%;\"\u003e\n \u003cp\u003eContinuous Improvement\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.2692%;\"\u003e\n \u003cp\u003e2.58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.1154%;\"\u003e\n \u003cp\u003eNeutral\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 7.69231%;\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 51.9231%;\"\u003e\n \u003cp\u003eEnd-of-phase review meetings\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.2692%;\"\u003e\n \u003cp\u003e3.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.1154%;\"\u003e\n \u003cp\u003eAgree\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 7.69231%;\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 51.9231%;\"\u003e\n \u003cp\u003eProject Performance\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.2692%;\"\u003e\n \u003cp\u003e2.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.1154%;\"\u003e\n \u003cp\u003eNeutral\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 2: Relationship between Project Management practices with project Performance\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"651\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 447px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 204px;\"\u003e\n \u003cp\u003eProject Performance\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 223px;\"\u003e\n \u003cp\u003eProject Planning\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 224px;\"\u003e\n \u003cp\u003ePearson Correlation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 204px;\"\u003e\n \u003cp\u003e.651\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 224px;\"\u003e\n \u003cp\u003eSig. (2-tailed)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 204px;\"\u003e\n \u003cp\u003e.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 224px;\"\u003e\n \u003cp\u003eN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 204px;\"\u003e\n \u003cp\u003e42\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 223px;\"\u003e\n \u003cp\u003eProject implementation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 224px;\"\u003e\n \u003cp\u003ePearson Correlation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 204px;\"\u003e\n \u003cp\u003e.779\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 224px;\"\u003e\n \u003cp\u003eSig. (2-tailed)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 204px;\"\u003e\n \u003cp\u003e.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 224px;\"\u003e\n \u003cp\u003eN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 204px;\"\u003e\n \u003cp\u003e42\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 223px;\"\u003e\n \u003cp\u003eProject Monitoring and evaluation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 224px;\"\u003e\n \u003cp\u003ePearson Correlation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 204px;\"\u003e\n \u003cp\u003e.592\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 224px;\"\u003e\n \u003cp\u003eSig. (2-tailed)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 204px;\"\u003e\n \u003cp\u003e.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 224px;\"\u003e\n \u003cp\u003eN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 204px;\"\u003e\n \u003cp\u003e42\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 223px;\"\u003e\n \u003cp\u003eProject Communication\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 224px;\"\u003e\n \u003cp\u003ePearson Correlation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 204px;\"\u003e\n \u003cp\u003e.666\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 224px;\"\u003e\n \u003cp\u003eSig. (2-tailed)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 204px;\"\u003e\n \u003cp\u003e.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 224px;\"\u003e\n \u003cp\u003eN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 204px;\"\u003e\n \u003cp\u003e42\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 223px;\"\u003e\n \u003cp\u003eStakeholder Involvement\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 224px;\"\u003e\n \u003cp\u003ePearson Correlation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 204px;\"\u003e\n \u003cp\u003e.249\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 224px;\"\u003e\n \u003cp\u003eSig. (2-tailed)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 204px;\"\u003e\n \u003cp\u003e.112\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 224px;\"\u003e\n \u003cp\u003eN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 204px;\"\u003e\n \u003cp\u003e42\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 223px;\"\u003e\n \u003cp\u003eDeveloping Effective Procedural Documentation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 224px;\"\u003e\n \u003cp\u003ePearson Correlation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 204px;\"\u003e\n \u003cp\u003e.189\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 224px;\"\u003e\n \u003cp\u003eSig. (2-tailed)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 204px;\"\u003e\n \u003cp\u003e.231\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 224px;\"\u003e\n \u003cp\u003eN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 204px;\"\u003e\n \u003cp\u003e42\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 223px;\"\u003e\n \u003cp\u003eContinuous Improvement\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 224px;\"\u003e\n \u003cp\u003ePearson Correlation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 204px;\"\u003e\n \u003cp\u003e.723\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 224px;\"\u003e\n \u003cp\u003eSig. (2-tailed)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 204px;\"\u003e\n \u003cp\u003e.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 224px;\"\u003e\n \u003cp\u003eN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 204px;\"\u003e\n \u003cp\u003e42\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 223px;\"\u003e\n \u003cp\u003eEnd of Phase Review Meetings\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 224px;\"\u003e\n \u003cp\u003ePearson Correlation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 204px;\"\u003e\n \u003cp\u003e.397\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 224px;\"\u003e\n \u003cp\u003eSig. (2-tailed)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 204px;\"\u003e\n \u003cp\u003e.009\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 224px;\"\u003e\n \u003cp\u003eN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 204px;\"\u003e\n \u003cp\u003e42\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 223px;\"\u003e\n \u003cp\u003eProject Performance\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 224px;\"\u003e\n \u003cp\u003ePearson Correlation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 204px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 224px;\"\u003e\n \u003cp\u003eSig. (2-tailed)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 204px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 224px;\"\u003e\n \u003cp\u003eN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 204px;\"\u003e\n \u003cp\u003e42\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 3: Multiple regression result\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"690\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"11\" valign=\"top\" style=\"width: 690px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eModel Summary\u003csup\u003eb\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 41px;\"\u003e\n \u003cp\u003eModel\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 53px;\"\u003e\n \u003cp\u003eR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003eR Square\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003eAdjusted R Square\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003eStd. Error of the Estimate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"5\" valign=\"top\" style=\"width: 314px;\"\u003e\n \u003cp\u003eChange Statistics\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003eDurbin-Watson\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003eR Square Change\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003eF Change\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 53px;\"\u003e\n \u003cp\u003edf1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 53px;\"\u003e\n \u003cp\u003edf2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003eSig. F Change\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 53px;\"\u003e\n \u003cp\u003e.904\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e.818\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e.774\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e.17867\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e.818\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e18.540\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 53px;\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 53px;\"\u003e\n \u003cp\u003e33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e1.792\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"11\" valign=\"top\" style=\"width: 690px;\"\u003e\n \u003cp\u003ea. Predictors: (Constant), End of Phase Review Meetings, Developing Effective Procedural Documentation, Project Monitoring and evaluation, Project Planning, Continuous Improvement, Stakeholder Involvement, Project Communication, Project implementation\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"11\" valign=\"top\" style=\"width: 690px;\"\u003e\n \u003cp\u003eb. Dependent Variable: Project Performance\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003eTable 4: Anova result\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"639\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"7\" valign=\"top\" style=\"width: 639px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eANOVA\u003csup\u003ea\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 162px;\"\u003e\n \u003cp\u003eModel\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 118px;\"\u003e\n \u003cp\u003eSum of Squares\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 82px;\"\u003e\n \u003cp\u003eDf\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003eMean Square\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 82px;\"\u003e\n \u003cp\u003eF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 82px;\"\u003e\n \u003cp\u003eSig.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 103px;\"\u003e\n \u003cp\u003eRegression\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 118px;\"\u003e\n \u003cp\u003e4.735\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 82px;\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e.592\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 82px;\"\u003e\n \u003cp\u003e18.540\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 82px;\"\u003e\n \u003cp\u003e.000\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 103px;\"\u003e\n \u003cp\u003eResidual\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 118px;\"\u003e\n \u003cp\u003e1.053\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 82px;\"\u003e\n \u003cp\u003e33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e.032\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 82px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 82px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 103px;\"\u003e\n \u003cp\u003eTotal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 118px;\"\u003e\n \u003cp\u003e5.788\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 82px;\"\u003e\n \u003cp\u003e41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 82px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 82px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"7\" valign=\"top\" style=\"width: 639px;\"\u003e\n \u003cp\u003ea. Dependent Variable: Project Performance\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"7\" valign=\"top\" style=\"width: 639px;\"\u003e\n \u003cp\u003eb. Predictors: (Constant), End of Phase Review Meetings, Developing Effective Procedural Documentation, Project Monitoring and evaluation, Project Planning, Continuous Improvement, Stakeholder Involvement, Project Communication, Project implementation\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003eTable 5: Multiple regression Coefficients result\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"660\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" rowspan=\"2\" valign=\"top\" style=\"width: 247px;\"\u003e\n \u003cp\u003eModel\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003eUnstandardized Coefficients\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003eStandardized Coefficients\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003eT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003eSig.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003eB\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003eStd. Error\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003eBeta\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"9\" valign=\"top\" style=\"width: 37px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 210px;\"\u003e\n \u003cp\u003e(Constant)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e.219\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e.308\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e.710\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e.482\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 210px;\"\u003e\n \u003cp\u003eProject Planning\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e.194\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e.085\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e.257\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e2.277\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e.029\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 210px;\"\u003e\n \u003cp\u003eProject implementation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e.138\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e.074\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e.279\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e2.875\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 210px;\"\u003e\n \u003cp\u003eProject Monitoring and evaluation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e.120\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e.047\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e.236\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e2.528\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e.016\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 210px;\"\u003e\n \u003cp\u003eProject Communication\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e.037\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e.072\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e.063\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e.508\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e.615\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 210px;\"\u003e\n \u003cp\u003eStakeholder Involvement\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e.113\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e.052\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e.247\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e2.161\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e.038\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 210px;\"\u003e\n \u003cp\u003eDeveloping Effective Procedural Documentation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e.008\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e.047\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e.014\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e.164\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e.871\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 210px;\"\u003e\n \u003cp\u003eContinuous Improvement\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e.264\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e.092\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e.322\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e2.869\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e.007\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 210px;\"\u003e\n \u003cp\u003eEnd of Phase Review Meetings\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e.278\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e.074\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e.407\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e3.734\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 6: Summary of hypothesis result\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"644\" class=\"fr-table-selection-hover\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 43px;\"\u003e\n \u003cp\u003eNo\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 386px;\"\u003e\n \u003cp\u003eHypothesis\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 133px;\"\u003e\n \u003cp\u003eResult\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 82px;\"\u003e\n \u003cp\u003eDecision\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 43px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 386px;\"\u003e\n \u003cp\u003eH1:\u0026nbsp;Project Planning has a positive relationship and statistically significant effect on the project performance.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 133px;\"\u003e\n \u003cp\u003e\u003cem\u003er=0.779/p=0.000\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eB=0.138/ p\u0026lt;0.01\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 82px;\"\u003e\n \u003cp\u003eAccepted\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 43px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 386px;\"\u003e\n \u003cp\u003eH2: Project implementation has a positive relationship and statistically significant effect on project performance\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 133px;\"\u003e\n \u003cp\u003e\u003cem\u003er=0.779/p=0.000\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eB=0.138/ p\u0026lt;0.01\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 82px;\"\u003e\n \u003cp\u003eAccepted\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 43px;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 386px;\"\u003e\n \u003cp\u003eH3: Project Monitoring and evaluation has a positive relationship and statistically significant effect on project performance\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 133px;\"\u003e\n \u003cp\u003e\u003cem\u003er=0.592/p=0.000\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eB=0.120/ p\u0026lt;0.05\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 82px;\"\u003e\n \u003cp\u003eAccepted\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 43px;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 386px;\"\u003e\n \u003cp\u003eH4: Project communication has a positive relationship and statistically significant effect on the project performance.\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 133px;\"\u003e\n \u003cp\u003e\u003cem\u003er=0.666/p= 0.003\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eB=0.037/ p\u0026gt;0.05\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 82px;\"\u003e\n \u003cp\u003eNot accepted\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 43px;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 386px;\"\u003e\n \u003cp\u003eH5: Stakeholder involvement has a positive relationship and statistically significant effect on project performance.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 133px;\"\u003e\n \u003cp\u003e\u003cem\u003er=0.249/ p=0.112\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eB=0.113/ p\u0026lt;0.05\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 82px;\"\u003e\n \u003cp\u003eaccepted\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 43px;\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 386px;\"\u003e\n \u003cp\u003eH6: developing effective procedural documentation has a positive relationship and statistically significant effect on project performance.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 133px;\"\u003e\n \u003cp\u003e\u003cem\u003er=0.189/p=0.231\u003c/em\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eB=0.008/ p\u0026gt;0.05\u0026nbsp;\u003c/em\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 82px;\"\u003e\n \u003cp\u003eNot accepted\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 43px;\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 386px;\"\u003e\n \u003cp\u003eH7: Continuous improvement has a positive relationship and statistically significant effect on project performance\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 133px;\"\u003e\n \u003cp\u003e\u003cem\u003er=0.723/p= 0.000\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eB=0.264/ p\u0026lt;0.01\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 82px;\"\u003e\n \u003cp\u003eAccepted\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 43px;\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 386px;\"\u003e\n \u003cp\u003eH8: End-of-phase review meetings have a positive relationship and statistically significant effect on project performance\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 133px;\"\u003e\n \u003cp\u003e\u003cem\u003er=0.397/p= 0.009\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eB=0.278/ p\u0026lt;0.01\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 82px;\"\u003e\n \u003cp\u003eAccepted\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"Addis Ababa University","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"End-of-phase Review Meetings, Project Communication, Project Management, Project Performance, Practices, stakeholder involvement","lastPublishedDoi":"10.21203/rs.3.rs-8292106/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8292106/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThis study examines the impact of project management practices on project performance at the Gibe-III project under Ethiopian Electric Power. A quantitative approach using descriptive and explanatory designs was applied, with data collected from 44 employees. Descriptive statistics revealed neutral responses across seven of eight practice dimensions, with end-of-phase review meetings scoring highest (M = 3.80). Regression analysis showed that 81.8% of performance variation was explained by the identified dimensions (R² = 0.818). Significant predictors included project planning (B = 0.194), implementation (B = 0.138), monitoring and evaluation (B = 0.120), stakeholder engagement (B = 0.113), continuous improvement (B = 0.264), and review meetings (B = 0.278). Procedural documentation and communication were not statistically significant. The study recommends strategic emphasis on planning, implementation, evaluation, continuous improvement, and review mechanisms to enhance project outcomes.\u003c/p\u003e","manuscriptTitle":"The effect of project management practice on project performance: In the case of Ethiopian Electric Power Gilgel Gibe-III project","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-12-09 06:11:57","doi":"10.21203/rs.3.rs-8292106/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"d181cde3-251f-4a57-b884-fa0cbf6bdbdc","owner":[],"postedDate":"December 9th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":59190935,"name":"Management"}],"tags":[],"updatedAt":"2025-12-09T06:11:57+00:00","versionOfRecord":[],"versionCreatedAt":"2025-12-09 06:11:57","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8292106","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8292106","identity":"rs-8292106","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}