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\title{Moderating Role of Stakeholders Attributes on Implementation of Rural Electrification Projects in Kenya}
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             \author[1]{Enock Kiage  Nyaboga}

             \author[2]{Prof. Iravo Mike  Amuhaya}

             \author[3]{Dr. Muchelule  Yusuf  Wanjala}

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\date{\small \em Received: 15 December 2019 Accepted: 4 January 2020 Published: 15 January 2020}

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\begin{abstract}
        


Stakeholders strongly influence the outcome of projects especially in complex projects with heterogeneous stakeholders, thus understanding their influence is essential to ensure project success and attainment of objectives. The benefits of rural electrification range from lighting, access to information, improved study environment for school children as well as improved businesses which in turn create employment opportunities and contribute to development and poverty reduction.

\end{abstract}


\keywords{project risk management; project planning; project leadership, }

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\let\tabcellsep& 	 	 		 
\section[{Introduction}]{Introduction}\par
takeholders can be divided into primary and secondary, which are further subdivided into social and non-social stakeholders. The shareholders and investors (owners), employees and managers, customers, local communities, suppliers, and other business partners are primary social stakeholders  {\ref (Carroll \& Buchholtz 3list, 2015)}. Their interests is an issue that can be monetary, professional, personal, or cultural, or can arise from a host of other motivations. They play a key role in project and programme activities and serve as key links with the general beneficiary population and also with donors and project facilitators. Project or programme stakeholders are those who have an interest in or are affected by a project or programme decisions \hyperref[b14]{(Donaldson \& Preston, 2009)}. The identification of stakeholders is critical and when the level of their power and influence are mapped, their impact on the project can be better understood. Stakeholders' engagement is measured by four indicators which include Level of engagement, Stakeholders' consultation, stakeholders' support, and stakeholder feedback.\par
There are two types of stakeholders: Primary stakeholders and secondary stakeholders. Primary stakeholders have a vested interest in how the organizations perform and the actions it engages into conduct business. On the other hand, secondary stakeholders can influence both positively and negatively, the actions of the organization. They indirectly affect the organization by taking actions to make it difficult for the organization to succeed or by supporting the organization's efforts  {\ref (Herevi, Coffey \& Trigunarsyah, 2015)}. Giving attention to project stakeholders is important to ensure the satisfaction of those involved or affected, which requires that procedural justice, legitimacy, and rationality have been met  {\ref (Alexander, 2000)}. This does not mean that all possible stakeholders must be involved, but the key stakeholders must be engaged. The choice of the key stakeholders in a project is inherently political, involves judgment, and usually has ethical consequences. In their study, Charles,  {\ref Antoine and Haarman (2006)}, argue that stakeholder participation enhances an organization's competitive advantage. Stakeholder participation improves ownership and support that can lead to a high up-take of project services, increased sustainability of benefits, and greater satisfaction. In such projects, the project manager needs to ensure the flow of information from the different organizations involved in the project  {\ref (Pinton \& Ndovic-Budic, 2007)}.\par
Stakeholders' management is paramount in the success of projects and organizations (Evan, William \& Edward, 2013). Even though minor decisions and S emergencies are generally not appropriate for stakeholder participation, a complex situation with farreaching impacts warrant stakeholder involvement and when done proactively, rather than in response to a problem, helps to avoid problems in the future \hyperref[b28]{(Maina, 2013)}. The focus of stakeholder participation is usually to share information with and gather input from, members of the public who may have an interest in a project. Eight components are the building blocks of stakeholders' engagement which include: stakeholder identification and analysis; information disclosure; stakeholder consultation; negotiation and partnerships; grievance management; stakeholder involvement in project monitoring; reporting to stakeholders; and management functions \hyperref[b39]{(PMI, 2014)}.\par
Project success has been measured in a variety of ways. While the measurement of project success has focused on tangibles, current thinking is that ultimately, project success is best judged by the stakeholders, especially the primary sponsor,  {\ref (Turner \& Zolin, 2012)}.  {\ref Shenhar and Dvir (2007)} suggested a model of success based on five dimensions, judged over different timescales.  {\ref Turner and Zolin (2012)} further suggested that at the end of the project you judge implementation by whether the scope is completed within the constraints of time and cost, and the project's output is delivered to specification, in the months following the project implementation is judged by whether the output performs as required and gives the desired benefit; and in the years following the project, implementation is judged by whether the organization achieves higherorder strategic objectives that improve organizational performance.\par
Proper implementation is key to the successful completion of all projects. Therefore it is important to apply the correct strategy depending on the type of project being implemented. The type of implementation strategy to be used on any project is supposed to be identified, developed, and tested before it is applied to ensure its success. However, these efforts have always been complicated by the use of inconsistent language and inadequate descriptions of implementation strategies in many works of literature. The expert recommendation for the best implementation strategy to use for any specific project is selected by systematically gathering input from a wide range of stakeholders with expertise in implementation science and clinical practice  {\ref (Powell, et al, 2015)}. Another important factor in the successful implementation of projects is ensuring collective responsibility among project stakeholders. This can be achieved through the generation of accurate designs by project professionals and proper estimation of costs and time which will in turn minimize the negative effects of economic instability on successful project delivery. Another necessary condition for successful project implementation is a commitment by clients to project financing obligations which motivates the contractors to commit themselves to project plans (Amade, Ogbonna, \& Kaduru, 2012). 
\section[{a) Rural Electrification Projects in Kenya}]{a) Rural Electrification Projects in Kenya}\par
Globally, 1,456 billion people have no access to electricity of which 83\% are in rural areas. This is no exception in Kenya where the majority of people in rural areas have no access to electricity and rely heavily on wood for cooking, which has adverse effects related to indoor pollution and health complications. Collecting firewood too takes a lot of time which mainly affects girl education as girls are the ones who usually collect firewood. In Sub-Saharan Africa, 12\% of the rural population have electricity which is far less than the 35.4\% average access to developing countries worldwide (Kenya national energy policy 2012). Kenya's efforts towards rural electrification are stipulated in the Government's Sessional Paper Number 4 on Energy (May 2004). This is the paper that laid the foundation for the formation of the Rural Electrification Authority (REA), which was charged with the responsibility of accelerating the pace of rural electrification in the country and ensure that affordable, cost-effective, and adequate quality energy sources are made available on a sustainable basis. REA was established in 2007 under Section 66 of the Energy Act of 2006 with the principal mandate of extending electricity supply to rural areas, managing the rural electrification fund, mobilizing resources for rural electrification, and promoting the development and use of renewable energy (MoE, 2013). In Kenya, therefore, rural electrification projects are mainly undertaken by the REA, though some works are carried out by Kenya Power Company (KPC), which also connects customers and operates and maintains the national grid. The objective of the REP, which is financed by the government, is to provide electricity in areas that are far from the national grid, and where electricity supply projects are not commercially viable, to improve the social and economic lives of Kenyans in those areas. 
\section[{b) Statement of the Problem}]{b) Statement of the Problem}\par
Implementation of rural electricity programs has been a challenge to the government with only 36\% of the rural population having access to electricity (the Republic of Kenya, 2013). Electrification in Kenya is below the SSA average with 15.8\% overall access and only 3.8\% access in rural areas. This is despite the establishment of the REA and the significant financing it receives, and other initiatives such as the Umeme Pamoja, a program launched in 2006/07 to get groups of rural households collectively connected to the grid. This low coverage is also in contrast with Vision 2030 where the government recognizes that the vision can only be achieved if citizens have access to electricity, including the rural areas. However, high connection costs and low incomes among rural households are some of the challenges facing rural electrification  {\ref (KPC, 2006)}. All electricity consumers pay a 5\% levy that goes towards the Rural Electrification Programme (REP).\par
However, despite this substantial source of income, the REP has not been able to increase the total electricity coverage proportionately with a total population of over 41million in Kenya, has a significantly low level of electricity supply, standing at 1500 Megawatt hour (MWh) compared to Finland with a population of around 5.5M but with energy supply of 400,000 MW (Abdulla and Markandya, 2007). Another comparison can be made with California which has a population of 38 million that is comparable to that of Kenya. But the comparison ends there because California has 41MW installed for every 1MW of Kenya's electricity power. Dufe (2015) focused on accessibility to rural electrification in Naivasha, whereas Mwiti (2014) focused on the influence of rural electrification on poverty eradication. According to REA (2014), despite access to electricity in Kieni standing at 46.7\% the connectivity level was less than 20\%. According to KPC in 2017, there was a challenge with customers' inability to load tokens in their meters where over 940,668 customers were affected. To add to that, the project has also been marred by procurement challenges that have affected the implementation a good example is the tender awarded to Bajaj Electricals and Wayne Homes that for the building and installation of electricity to seven counties that were contested. 
\section[{c) The objective of the study}]{c) The objective of the study}\par
The purpose of this study was to establish the role of stakeholders' management on the implementation of rural electrification projects in Kenya.\par
To achieve the objective of the study, the researcher used the following hypothesis. Ho 1 : Project risk management has no significant role in the implementation of rural electrification projects in Kenya. Ho 2 : Project planning has no significant role in the implementation of rural electrification projects in Kenya. Ho 3 : Project leadership has no significant role in the implementation of rural electrification projects in Kenya. Ho 5 : Stakeholder attributes do not have a significant moderating role in the implementation of rural electrification projects in Kenya. 
\section[{II.}]{II.} 
\section[{Literature Review}]{Literature Review}\par
The theoretical framework in this study consisted of theories and models that relate to stakeholders management which include: Complexity and Chaos Theories; Principal-Agent Theory, Culture Theory, and Stakeholders Theory. Complexity theory was originally an invention of Los Alamos nuclear laboratory, in Santa Fe Institute in Mexico in the USA starting in the early 1980s, where the scientists claimed that through the study of theory one can see both laws of chaos and that of order, through which an explanation for how any collection of components will organize itself can be generated. This theory stipulates that systems are best regarded as wholes and studied as such thus rejecting the traditional emphasis on simplification and reduction as inadequate techniques. The complexity theory was founded on an attempt to rationalize the behavior of large and complex systems, believing they cannot be explained by usual rules of nature \hyperref[b47]{(Sherman \& Ralph, 1998)}. Complexity theory states that critically interacting components self-organize to form potentially evolving structures exhibiting a hierarchy of emergent system properties \hyperref[b27]{(Lucas, 2009)}. Complexity theory is concerned with the study of how order, structure, pattern, and novelty arise from extremely complicated, apparently chaotic systems and conversely, how complex behavior and structure emerge from simple underlying rules. Complexity theory describes states varying from comparative order to complete disorder, or chaos, or where the system defies prediction or control. It is the recognition that projects or processes do not behave predictably, even when under the guidance of experienced teams or groups, whereas some parts will be very stable and behave predictable manner that has sustained continued interest in complexity theory \hyperref[b41]{(Remington \& Zolin, 2011)}.\par
The Principal-Agent theory was propounded by Stephen Ross  {\ref (1972)} where he tried to explain how best to organize the relationship of the owner of resources in a project (Principal) and the person appointed or contracted to work on behalf of the principal (Agent). The success of any given project is heavily dependent on the relationship and understanding of the major stakeholders or the major parties in a contract. The theory has three assumptions; the agent is always selfinterested, risk-averse, and possesses knowledge that most of the time isn't available to the Principal. For the project to be successful, the assumption is that the stakeholders cooperate and exchange vital information to ensure the project goals are achieved. Thus communication is key to any success of the project else it becomes a major risk \hyperref[b5]{(Ceric, 2003)}. According to \hyperref[b43]{Schieg (2008)}, the agent mostly tries to maximize his/her benefit even if it means having higher damage to the client. The principal-agent theory explains this problem by characterizing three issues in the relationship which are: adverse selection, hold up, and moral hazard.\par
Stakeholder's theory can be traced back when  {\ref Freeman (1984)} defined a stakeholder as any group or individual who can affect or is affected by the achievement of an organization's objectives. The origin of the theory is strategic management but \hyperref[b8]{Cleland (1986)} introduced stakeholder thinking in project management that projects have diverse stakeholders with their objectives, interests, and expectations which result in conflicts. According to PMI (2014), stakeholders are critical in projects, and the project management process is an adaptation of specifications, plans, and various approaches and techniques following the expectations of various stakeholders. Stakeholders' theory provides a framework for understanding and categorizing project stakeholders as a strategy to easily manage them to provide the necessary influence in a given project. In project management, stakeholders can be categorized based on their roles in a given project, their involvement and the nature of their relationship within the project, and finally based on the degree of risk they pose to the project (PMI, 2014). According to \hyperref[b32]{Mitchell, et al (1997)} the importance of stakeholders can be determined by their legitimacy, power, and their influence on a project outcome. 
\section[{III.}]{III.} 
\section[{Conceptual Framework}]{Conceptual Framework}\par
The conceptual framework of the study is presented in figure  {\ref 1} below. 
\section[{Independent variables moderating variable Dependent variable}]{Independent variables moderating variable Dependent variable} 
\section[{Conceptual framework}]{Conceptual framework}\par
IV. 
\section[{Empirical Review}]{Empirical Review}\par
The empirical literature on the relationship between project leadership, project risk management, project planning, and project implementation is as follows:a) Project Risk Management and Project implementation\par
According to \hyperref[b36]{Nocco and Stulz (2006)}, Risk management involves the identification, measurement, monitoring, and controlling of risk to ensure that the individual responsible for the risk clearly understands it and the organization's exposure is within the limits established by management; the appropriate risk-taking decisions are in line with business strategy and objectives set by management; the expected payoffs compensate for the risk taken are clear; the risk-taking decision is explicit and clear; sufficient capital as a buffer is available to take the risk. The goal of risk management is to optimize risk-reward trade-off. Financial institutions should have in place a risk management framework that encompasses the scope of risks to be managed, the processes/systems and procedures to manage risk, the roles and responsibilities of individuals involved in risk management. The framework should be comprehensive enough to capture all risks a bank is exposed to and have the flexibility to accommodate any change in business activities \hyperref[b36]{(Nocco \& Stulz, 2006}  Van?k et al, (2013) explained that risk assessment is an important part of the assessment of an investment project as underestimating the risks leads to an erroneous decision with negative consequences on the economy of the project. However, they argued that due to the level of investment and time factor related to company conditions, risk gains it's important and most of the time managers of companies approach risk assessment based on suspicion rather than the use of required methods. Further, Van?k et al (2013) concluded that there are four basics phases to the risk assessment process: asset identification; threats identification and their relationships; determination of significance; and risk determination based on nature or purpose. the result from the process is a recommended decision with the consideration of accurate risk assessment. Organizations are focusing on is increasing their employees' awareness of risk management and making better risk-based decisions. This is implemented through education and training at the appropriate levels in the organization. 
\section[{b) Project Planning and Project implementation}]{b) Project Planning and Project implementation}\par
According to  {\ref Harold (2003)} and Rosario (2000), stakeholder involvement in planning entails the involvement of stakeholders on how to plan, development of scope, team selection planning, and identification of deliverables, developing the work breakdown structure (WBS) resource requirement estimates, cost estimation, schedule development, risk planning, budgeting and approval of project commencement. \hyperref[b15]{Dvir, Raz and Shenhar (2003)} in their study of the relationship between project planning and project success, revealed that project success was insensitive to the implementation level of management processes. Project success is correlated to project planning specifically requirements definition planning and technical specifications development. They believe that through planning does not guarantee the success of the project, a minimum level of planning is necessary with an emphasis on the planning tools and procedures. The project manager has the responsibility of the formal planning while requirements development and specifications are dependent on the overall cooperation with the end-user of the project. Since projects are unique, the precise initial stage of planning where all the activities needed to be carried out for the completion of projects, their cost is duration are difficult or even sometimes impossible to be known. To aggravate the issue is where activities are dependent on other activities for the outcome. It with such reason that some authors believe that planning isn't crucial and helpful for the overall project success \hyperref[b15]{(Dvir, Raz, \& Shenhar, 2003)}. 
\section[{c) Project leadership and project implementation}]{c) Project leadership and project implementation}\par
Limsila \& Ogunlana(2008) examined the relationship between the project manager's leadership style, subordinates' commitment, and work performance in Thailand's construction industry. The study found out that the project managers switch styles based on the project needs. Transformational leadership was found to be the dominant style in Thailand and influence a higher subordinates' commitment to giving higher leadership outcomes in terms of effectiveness, satisfaction, and extra efforts. This is because the culture of Thailand is more democratic that encourages subordinates to be participative. \hyperref[b35]{Muller and Turner (2007)} investigated the impact of the project manager's style on project success. The study found out that the project manager's leadership competencies influenced project success. Emotional competence was found to be a significant contributor to project success in all projects, whereas managerial competence was a significant contributor to some projects, and intellectual competence was negatively correlated with project success. Emotional resilience and communication were found to be key teamwork aspects important for projects of medium complexity while for high complexity projects sensitivity was found to be key concluding that transformational leadership as the appropriate style for projects which concurs with Keegan and Den Hartog (2004). 
\section[{d) Stakeholders attributes and project implementation}]{d) Stakeholders attributes and project implementation}\par
Stakeholder buy-in is very essential as it guarantees the successful implementation of projects. Any project that is implemented without the blessing of the key stakeholders like the sponsors is a waste of time and money. It is therefore essential that stakeholders are identified before the start of any project to allow for buyin into project activities and its intended objectives (Duncan, 2018). Well-aligned stakeholders will support the project activities, provide support and resources during challenging times. During the implementation of any project, many stakeholders are involved. Along the process aiming at completing the project, stakeholders can be partners, resources, or roadblocks but potentially they are all the three rolled into one. Stakeholder buy-in, the cooperation, or the positive participation of a stakeholder, is the preferred condition for any successful project (May, 2016).Alexander, (2018) noted that since there are quite a variety of stakeholders who are involved in projects buy-in becomes a difficult task to quantify. Projects may seem to be advancing well, but without full buy-in from key stakeholders, it might suddenly take a sharp turn for the worst, risking the final deliverables and customer satisfaction. The stakeholder buy-in can be increased by identifying what motivates stakeholders, focusing on telling the truth, even when it isn't what stakeholders want to hear, making sure stakeholders understand their contribution to a project, reaffirming goals and communicating progress throughout execution, remaining consistent, and providing positive feedback after the project ends (Alexander, 2018). Across all organizations within different industries, projects and programs of different sizes succeed or fail mostly due to having the right levels of team commitment, stakeholder buy-in, and executive support. Project managers will always strangle to manage the project successfully so long as these key components are absent  {\ref (Aziz, 2014)}  
\section[{Methodology}]{Methodology}\par
This study used a descriptive research design that deals with the what, where, and how of a phenomenon, which was guided by hypothesis and focused on the frequency with which something occurs and the relationship between the variables (Bernard, 2012). The study also used an explanatory research design that looks for explanations on the nature of certain relationships and investigates the cause-effect relationship between variables  {\ref (Saunders, 2009)}.The positivism research philosophy was used for this study since the choice depends on the research hypothesis to be tested. This was based on the fact that positivism reflects the belief that reality is stable and that it can be observed and described from an objective viewpoint without interfering with phenomena (Matta, 2015). The target population for this study comprised of 20,299 REA projects implemented in Kenya public primary schools. The sample size was determined by the adoption of Yamane sample size determination (Yamane, 1967) where 392 projects were selected. In this study, the data collected was analyzed using both descriptive and inferential statistics. Descriptive statistical techniques which are frequency distributions, means, and standard deviations were used to analyze the data to be collected. Inferential statistical analysis was undertaken which included hypothesis testing. Independent variables will be subjected to the following tests: linearity, multicollinearity, normality, homoscedasticity to satisfy ordinary least square (OLS) assumptions. The relationship between the dependent variable and independent variables was done by the use of univariate and multiple regressions to establish a relationship. The linear predictor function will be as follows:Y = ? 0 + ? 1 X 1 + ? 2 X 2 + ? 3 X 3 + ? 4 X 4 + ? Y = ? 0 + ? 1 X 1 * M + ? 2 X 2 * M + ? 3 X 3 * M + ? 4 X 4 * M + ? .\par
Where: Y = project implementation? 0 = Constant ? 1 = regression coefficient of educational diversity ? 2 = regression coefficient of socio-cognitive diversity ? 3 = regression coefficient of gender diversity ? 4 = regression coefficient of physical disability diversity X 1 =risk management X 2 =project planning X 3 =project leadership X 4 
\section[{=monitoring and controlling M = Moderator (stakeholders attributes) e = error terms/residual}]{=monitoring and controlling M = Moderator (stakeholders attributes) e = error terms/residual}\par
The study tested the hypotheses using regression analysis to establish the role of stakeholders in the implementation of the rural electrification project in Kenya by using a P-value approach at 0.05 level of significance. 
\section[{VI.}]{VI.} 
\section[{Results}]{Results} 
\section[{a) Response Rate}]{a) Response Rate}\par
The study selected a sample of 392project managers representing an implemented school project. All selected respondents were issued with questionnaires for data collection but the researcher was able to receive back only 347 questionnaires. The returned questionnaires formed a response rate of 88.5\% According to \hyperref[b33]{Mugenda and Mugenda (2013)}, a response rate of 50\% and above is good for analysis and reporting, that of 60\% is sufficient while 70\% and above is excellent. 
\section[{b) Descriptive Statistics}]{b) Descriptive Statistics}\par
In this section, the study presents findings on Likert scale questions where respondents were asked to indicate their level of agreement or disagreement with various statements that relate to the role of stakeholders' management on the implementation of rural electrification projects in Kenya. The article focused on project risk management, project leadership, project planning, and the moderating effect of stakeholders 
\section[{c) Project Risk Management}]{c) Project Risk Management}\par
The study showed that project risk management influenced the implementation of the project as indicated by the mean of 3.8. Specifically, the findings showed that the respondents agreed that project stakeholders are involved in the risk identification process (M=3.982, SD=1.370); the risk registers are available and accessible to all stakeholders of the project (M=3.948. SD=1.263); and that problem analysis is done to identify the role and contribution of various stakeholders towards the success of the project (M=3.889, SD=1.381). The study also established that the respondents agreed that the stakeholders are involved in monitoring the project risks (M=3.863, SD=1.326); that stakeholder analysis is done to identify the extent of decision making (M=3.777, SD=1.275); once risks are identified mitigation measures are documented (M=3.738, SD=1.320); and that mitigation measures and strategies are communicated to the various stakeholders (M=3.698, SD=1.331).The study findings agree with \hyperref[b36]{Nocco and Stulz (2006)}, that risk management involves the identification, measurement, monitoring, and controlling of risk to ensure that the individual responsible for the risk clearly understands it and the organization's exposure is within the limits established by management; the appropriate risk-taking decisions are in line with business strategy and objectives set by management; the expected payoffs compensate for the risk taken are clear; risk-taking the decision is explicit and clear. The respondents also suggested other methods to deal with risk which include; planning, effective communication, and keeping records of all the risks. The respondents also identified some challenges related to the handling of project risks. Failure in monitoring and managing risks, lack of clear goals, and inadequate communications. 
\section[{d) Project Planning}]{d) Project Planning}\par
The study found that project planning influenced the implementation of projects as indicated with a mean of 3.920 an indication that the respondents agreed with the statements about stakeholders' role in project planning on implementation of rural electrification projects in Kenya. The findings specifically showed that the respondent agreed that planning of new projects is a collective responsibility that involves all the stakeholders of the project (M=3.994, SD=1.476); planning tools like PERT, CPM, GANTT CHARTS, WBS are used (M=3.961, SD=1.476); and that the project charter is the overall project reference document used (M=3.955, SD=1.546). The study further showed that respondents agreed that they estimate the resources for the project activities (M=3.915, SD=1.343); the stakeholders participate in the development of the project management plan (M=3.856, SD=1.525); and that stakeholders are involved in the identification of the activities needed to complete deliverables (M=3.836, SD=1.220). These study findings concur with Harold (2003) and Rosario (2000) that stakeholder involvement in planning entails the involvement of stakeholders on how to plan, development of scope, team selection planning, and identification of deliverables, developing the work breakdown structure (WBS) resource requirement estimates, cost estimation, schedule development, risk planning, budgeting and approval of project commencement. It also agrees with Dvir, Razand \hyperref[b15]{Shenhar (2003)} that planning reduces uncertainty and increases the likelihood of project success. Project success is correlated to project planning specifically requirements definition planning and technical specifications development. The study also suggested other methods applicable to the planning process in the organization. During the planning process, they first establish their objectives; evaluating their current and expected financial situation, and then determine whether the available resources met the objective; and finally, conduct an environmental scan. The study also identified some of the challenges in planning which include: not implementing the plan; involvement of the right people in the planning process; regular feedback from participants; and finally building of accountability. 
\section[{e) Project Leadership}]{e) Project Leadership}\par
The study proved that project leadership influenced the implementation of projects as shown by a mean of 3.919 an indication that on average, the respondents agreed with the various statements on stakeholders' role in project leadership on the implementation of rural electrification projects in Kenya. The findings also show that the respondents were in strong agreement that all projects relevant stakeholder is provided by the projects updates information (M=4.007, SD=1.251). Also, the respondents agreed that: the project manager has put in place a clear and effective communication plan with the project stakeholders' (M=3.994, SD=1.343); stakeholders believe the project manager has the necessary knowledge and skills needed to attain the success of the project (M=3.988, SD=1.475); and that there is the proper social interaction among stakeholders depending on their influence in the project (M=3.961, SD=1.674). Furthermore, the study found the respondents agreed that stakeholders are involved in the processes of the entire project decision making concerning appointing the project leader (M=3.836, SD=1.426); the project leader has developed a Stakeholders register that shows all the project stakeholders (M=3.830, SD=1.441); and that in dealing with project stakeholders' the project manager applies different leadership styles (M=3.817, SD=1.142). The study findings agree with the findings of \hyperref[b35]{Muller and Turner (2007)} that the project manager's leadership competencies influenced project success. Emotional competence is a significant contributor to project success in all projects. Therefore, managerial competence is a significant contributor to some project success. It also agrees with the findings of Limsila and Ogunlana (2008) that transformational leadership was found to be the dominant style and influence a higher subordinates' commitment to giving higher leadership outcomes in terms of effectiveness, satisfaction, and extra efforts. The challenges incurred by leadership in the project include too few team members; lack of morale and motivation; lackluster bucking from key partners; unclear expectations; and lack of training. 
\section[{f) Stakeholder Attributes}]{f) Stakeholder Attributes}\par
The findings proved that stakeholders' attributes have a moderating effect on the implementation of rural electrification projects in Kenya as indicated by a mean of 3.878. The study also established that the interest of all key stakeholders has always been taken into consideration during the implementation of rural electrification projects in Kenya (M=3.961, SD=1.149); the assessment of the proximity of all stakeholders is key to the implementation of rural electrification projects in Kenya (M=3.955, SD=1.199); and that stakeholders legitimacy has been considered during the implementation of rural electrification projects in Kenya (M=3.836. SD=1.234). The study further found that the respondents agreed that stakeholders participate in key decisions of the project (M=3.836, SD=1.313); and that the main objective of any project is to meet or exceed the expectations of its stakeholders due to their influence (M=3.803, SD=1.248). These findings are in agreement with Duncan (2018) that stakeholders must be identified before the start of any project to allow for buy-in into project activities and its intended objectives. He added that well-aligned stakeholders will support the project activities, provide support and resources during challenging times. The finding also concurs with Alexander, (2018) that without full buy-in from key stakeholders, projects might suddenly take a sharp turn for the worst, risking the final deliverables and customer satisfaction. Financial stakeholders, such as unions and materials suppliers, can use their influence and production to demand greater financial benefit. Contractors can negatively affect the project through time and cost overruns. When a delay is caused by a special-interest group, it can increase the cost of the project by adding the expense of legal proceedings. Political stakeholders can also use the project to ingratiate themselves to voting blocks and political donors. 
\section[{g) Project Implementation}]{g) Project Implementation}\par
The findings gave an aggregate mean score of 3.894. This is an indication that on average, the respondent's greed with the statements about the rate of project implementation. The study found that the respondents agreed that the major stakeholders determine the standards of the project (M=4.021, SD=1.265); end-user satisfaction is the overall criteria for the success of a project (M=3.988, SD=1.182); and that the project records show that the project was according to budget (M=3.902, SD=1.235). The findings further showed that the respondents agreed that the majority of the projects are completed on time and successfully (M=3.902, SD=1.235); the project satisfies the End-user operational needs (M=3.896, SD=1.21); that stakeholders believe that project resources were well utilized as scope, schedule (M=3.81, SD=1.142) and that concluded projects normally meet the required quality/standard (M=3.738, SD=1.168). The findings agree with Flanagan and Norman (2003) that project implementation is important as it helps ensure that a given project is implemented within its desired budget, schedule, the accepted quality standards, functionality, as well as the fitness of purpose. It also concurs with Kululanga and Kuotcha (2010) that project implementation ensures that enterprises maximize profitability, minimize the consequences of risky and uncertain events in terms of achieving the project's objectives, and seizes the chances of the risky events from arising. 
\section[{VII.}]{VII.} 
\section[{Inferential Analysis a) Correlation Analysis}]{Inferential Analysis a) Correlation Analysis}\par
Pearson R correlation wad used to measure the strength and direction of the linear relationship between variables. The association was considered to be: small if ±0.1 <r< ±0.29; medium if ±0.3 <r<±0.49; and strong if r>±0.5. .000\par
The findings in Table \hyperref[tab_2]{1} show that project risk management had a strong positive and significant relationship with project implementation (r=0.793, p=000). The p-value was less than the significance level 0.05) an indication that the relationship was significant. The findings also show that project planning ad project implementation has a strong positive relationship (r=0.743). The relationship was considered significant since the p-value (0.000) was less than the selected level of significance. Besides, project leadership is seen to have a strong positive, and significant relationship with project implementation (r=0.846). The relationship between these variables was significant since the p-value (0.000) was less than the selected level of significance (0.05). Finally, the relationship between project monitoring and control project implementation is seen to be strong and positive (r=0.808). The relationship is also considered to be significant as indicated by a p-value (0000) less than the significance level (0.05). These findings, therefore, suggest that the independent variables (project risk management, project planning, project leadership, and project monitoring and control) have a significant relationship with project implementation. To further understand the relationship between these variables, the study computed regression analysis. 
\section[{b) Testing Multiple Linear Regression Assumptions}]{b) Testing Multiple Linear Regression Assumptions}\par
Diagnostic tests were performed to test the assumptions of linear regression. The assumptions tested were normality, multicollinearity, and Homoscedasticity. 
\section[{c) Normality Test}]{c) Normality Test}\par
Normality was tested by the use of the Shapiro Wilk Test. The nullhypothes is for this test is that the population is normally distributed. Thus if the p-value is less than the chosen alpha level (0.05), then the null hypothesis is rejected and there is evidence that the data tested are not from a normally distributed population. From the findings, all variables had p-values greater than 0.05. This shows that they were all normally distributed and hence the data meets the regression analysis assumption of normality. 
\section[{Multicollinearity}]{Multicollinearity}\par
Variance Inflation Factor (VIF) was used, which measures multicollinearity in the regression model. The VIF values found in Table \hyperref[tab_4]{3} show that there was minimal multicollinearity among the independent variables since all the values are below 5. This implies that the results of the multiple regression equation are not misleading, since the independent variables in the multiple regression equation are not highly correlated among themselves. 
\section[{e) Homoscedasticity}]{e) Homoscedasticity}\par
In this study, Heteroscedasticity was tested by performing the Breuch-pagan / cook-Weisberg test. Breusch-Pagan / Cook-Weisberg test the null hypothesis that the error variances are all equal versus the alternative that the error variances are a multiplicative function of one or more variables  {\ref (Vinod, 2008)}. Table \hyperref[tab_5]{4} above shows that the constant variance (Chi 2 = 2.6874) is insignificant (P = 0.541). Therefore, there is no instance of heteroscedasticity in the data and therefore multiple regression findings were not misleading. The study computed regression analysis to establish the role of stakeholders' management in the implementation of rural electrification projects in Kenya. 
\section[{f) Regression Analysis}]{f) Regression Analysis}\par
Univariate analysis was computed to test the relationship between each independent variable on the dependent variable. The findings were also used to test the study research hypothesis. 
\section[{g) The Role of Project Risk Management on the Implementation of Rural Electrification Project}]{g) The Role of Project Risk Management on the Implementation of Rural Electrification Project}\par
The study computed univariate analysis to assess the role of project risk management on the implementation of rural electrification projects. The hypothesis tested was: Ho 1 : Project risk management has no significant role in the implementation of rural electrification projects in Kenya.\par
The findings were discussed in three tables. Adjusted R 2 shows the variation in the dependent variable due to changes in the independent variable. Table \hyperref[tab_6]{5} shows that adjusted R squared was 0.601; this is an indication that at a 95\% confidence interval, 60.1\% variation in project implementation can be attributed to project risk management. The remaining 39.9\% suggest that other factors can explain changes in project implementation that were not discussed in this model. R is the correlation coefficient which shows the relationship between the study variables. There was a strong positive relationship between project risk management and project implementation as shown by 0.793. From the ANOVA table 6, the p-value obtained was 0.000 which is less than the selected significance level of 0.05 which suggests that the model was significant and therefore the data was ideal for concluding the population parameters. F-critical value (3.868), obtained from F-distribution tables, was less than the F-calculated value (13.769) i.e. 3.868<1349.598. Since the F-calculated value was greater than the F-critical value, it suggests that project risk management significantly influences project implementation. The regression equation was:Y = 0.670 + 0.646 X 1\par
The above regression equation shows that holding project risk management to a constant zero, project implementation will be at a constant value of 0.670 units. The influence of project risk management on project implementation was significant. This is because the p-value obtained (0.000) was less than the selected level of significance (0.05). Therefore, a unit increase in project risk management would lead to an increase in project implementation of rural electrification projects in Kenya by 0.646. Therefore we reject the null hypothesis that "Project risk management has no significant role in the implementation of rural electrification project in Kenya". 
\section[{h) The Role of Project Planning on the Implementation of Rural Electrification Project}]{h) The Role of Project Planning on the Implementation of Rural Electrification Project}\par
The study computed univariate analysis to determine the role of project planning on the implementation of rural electrification projects in Kenya. The hypothesis tested was: Ho 2 : Project planning has no significant role in the implementation of rural electrification projects in Kenya.  From the ANOVA table, the F-calculated value was 4.247 and was significant at a p-value of 0.000. The F-critical value obtained from the F-distribution tables was 3.868. The findings showed that the f critical value was less than the f calculated value (3.868<4.247). This, therefore, suggests that project planning influences project implementation of rural electrification projects in Kenya. Since the p-value (0.000) was less than the selected level of significance (0.05), it suggests that the model was significant and therefore the data was the idea for concluding the population parameters. The regression equation was: Y = 1.102 + 0.602 X 2 The above regression equation revealed that holding project planning to a constant zero, project implementation will be at a constant value of 1.102 units. The influence of project panning on project implementation was significant as indicated by a p-value (0.00), less than the sleeted level of significance (0.05). Therefore, a unit increase in project planning would lead to an increase in project implementation of rural electrification projects in Kenya by 0.602 units. Therefore we reject the null hypothesis that "Project planning has no significant role in the implementation of rural electrification project in Kenya". 
\section[{i) The Role of Project Leadership on the Implementation of Rural Electrification Project}]{i) The Role of Project Leadership on the Implementation of Rural Electrification Project}\par
The study computed univariate analysis to establish the role of project leadership in the implementation of rural electrification projects in Kenya. The hypothesis tested was: Ho 3 : Project leadership has no significant role in the implementation of rural electrification projects in Kenya. From the model summary, the value of adjusted R 2 was found to be 0.527 which suggests that 52.7\% variation in project implementation can be explained by changes in project planning. The remaining 47.3\% suggest that other factors can be attributed to changes in project implementation of rural electrification projects in Kenya. The findings further reveal that the variables in this model (project planning and project implementation) are strongly and positively related as indicated by the correlation coefficient (R) value of 0.727.\par
From the model summary, the value of adjusted R 2 was found to be 0.674 which suggests that 67.4\% variation in project implementation can be explained by changes in project leadership. The remaining 32.6\% suggest that other factors can be attributed to the implementation of the rural electrification project in Kenya. The correlation coefficient denoted by R usually shows the relationship existing between the study variables. The findings show that the variables were strongly and positively related as indicated by 0.846. From the ANOVA table, the study found a pvalue of 0.000 which is less than the selected level of significance which is 0.05. This, therefore, suggests that the model is significant and that the data used is suitable for concluding the population parameters. The findings further showed that the value of f-calculated was 12.700. The f-critical value obtained from the f critical tables was 3.868. From the findings, the fcalculated value is greater than the f-critical value (12.7>3.868). This, therefore, suggests that project leadership influences the implementation of rural electrification projects in Kenya. The above regression equation shows that holding project leadership to a constant zero, project implementation will be at a constant value of 1.360 units. The findings also show that project leadership has a significant influence on project implementation. The influence was significant since the p-value (0.000) was less than the selected level of significance (0.05). Therefore, a unit increase in project leadership would lead to a decrease in the implementation of rural electrification projects in Kenya by 0.695 units. Therefore we reject the null hypothesis that "Project leadership has no significant role in the implementation of rural electrification project in Kenya". 
\section[{j) The Moderating Role of Stakeholder Attributes on the Implementation of Rural Electrification Project}]{j) The Moderating Role of Stakeholder Attributes on the Implementation of Rural Electrification Project}\par
A stepwise regression analysis was conducted to establish the moderating role of stakeholder attributes on the implementation of rural electrification projects in Kenya. The hypothesis tested was: Ho 5 : Stakeholder attributes do not have a significant moderating role in the implementation of rural electrification projects in Kenya. The model summary for the moderated equation was used to show the amount of variation in the dependent variable that could be explained by the moderated variables. The findings show that after the introduction of stakeholders attributes as the moderating variable, the value of adjusted R square increased from 0.762 to 0.780 an indication that the moderated variable explains 78\% variations in project implementation. The remaining 22\% suggest that other factors can be used to explain variations in the performance of affordable housing programs in Kenya that were not included in the model. This tested the significance of the moderated model. The significance was tested at a 5\% level of significance. The findings presented in Table \hyperref[tab_16]{15} show that the models had a significance level of 0.000; both models the un-moderated and the moderated models. From the findings, the F-calculated for the first model was 15.585and the second model was 17.579. Since the F-calculated for the two models were more than the Fcritical, 2.398 (first model) and 1.966 (second model), the two models were a good fit for the data and hence they could be used in predicting the moderating role of stakeholder attributes on the implementation of rural electrification project in Kenya. The findings showed that Project Risk Management* Stakeholders Attributes had a significant influence on the implementation of rural electrification projects in Kenya (?=0.259, p=0.000). Since the pvalue was less than the selected level of significance (0.05), the study concluded that the influence was significant. The study, therefore, rejected the null hypothesis H 051 Stakeholder attributes do not have a significant moderating role of project risk management on the implementation of rural electrification project in Kenya.\par
Project Planning* Stakeholders Attributes were seen to have a positive influence on the implementation of the rural electrification project in Kenya (?=0.414, p=0.007). The influence was considered significant since the p-value obtained (0.007) was less than the selected level of significance (0.05). The study thus rejects the null hypothesis H 052 Stakeholder attributes do not have a significant moderating role of project planning on the implementation of rural electrification project in Kenya.\par
Project Leadership* Stakeholders Attributes had a positive influence on the implementation of the rural electrification project in Kenya (?=0.428, p=0.023). The p-value obtained (0.023) was less than the selected level of significance (0.05) therefore suggesting a significant influence. The study thus rejects the null hypothesis H 053 Stakeholder attributes do not have a significant moderating role of project leadership on the implementation of rural electrification project in Kenya. 
\section[{k) Summary of Findings}]{k) Summary of Findings}\par
The study was guided by the following specific objectives: To assess the role of project risk management on the implementation of rural electrification project in Kenya; to determine the role of project planning on the implementation of rural electrification project in Kenya; to establish the role of project leadership on the implementation of rural electrification project in Kenya, and to establish the moderating role of stakeholder attributes on the implementation of rural electrification project in Kenya. 
\section[{l) The Role of Project Risk Management on the Implementation of Rural Electrification Project}]{l) The Role of Project Risk Management on the Implementation of Rural Electrification Project}\par
The study found that project stakeholders are involved in the risk identification process; the risk registers are available and accessible to all stakeholders of the project, and that problem analysis is done to identify the role and contribution of various stakeholders towards the success of the project. The study also established that the stakeholders are involved in monitoring the project risks; that stakeholder analysis is done to identify the extent of decision making; once risks are identified mitigation measures are documented, and that mitigation measures and strategies are communicated to the various stakeholders. The study findings agree with \hyperref[b36]{Nocco and Stulz (2006)}, that risk management involves the identification, measurement, monitoring, and controlling of risk to ensure that the individual responsible for the risk clearly understands it and the organization's exposure is within the limits established by management; the appropriate risk-taking decisions are in line with business strategy and objectives set by management; the expected payoffs compensate for the risk taken are clear; the risk-taking decision is explicit and clear; sufficient capital as a buffer is available to take the risk. The goal of risk management is to optimize risk-reward trade-off. 
\section[{m) The Role of Project Planning on the Implementation of Rural Electrification Project}]{m) The Role of Project Planning on the Implementation of Rural Electrification Project}\par
The study established that planning of new projects is a collective responsibility that involves all the stakeholders of the project; planning tools like PERT, CPM, GANTT CHARTS, WBS are used; and that the project charter is the overall project reference document used. The study further showed that project managers estimate the resources for the project activities; the stakeholders participate in the development of the project management plan; and that stakeholders are involved in the identification of the activities needed to complete deliverables. These study findings concur with Harold (2003) and Rosario (2000) that stakeholder involvement in planning entails the involvement of stakeholders on how to plan, development of scope, team selection planning, and identification of deliverables, developing the work breakdown structure (WBS) resource requirement estimates, cost estimation, schedule development, risk planning, budgeting and approval of project commencement. It also agrees with  {\ref Dvir, Razand Shenhar (2003)} that planning reduces uncertainty and increases the likelihood of project success. Project success is correlated to project planning specifically requirements definition planning and technical specifications development.\par
The study also established other methods applicable to the planning process in the organization. They explained that during the planning process, they first establish their objectives. They evaluate their current and expected financial situation and then determine whether the available resources met the objective. Also, they indicated that it is important to conduct an environmental scan. This scan usually involves considering various driving forces, or major influences, that might affect the organization. Analyzing the situation is also an important step; usually through SWOT analysis (strengths, weaknesses, opportunities, and threats) faced by the organization. Once the situation has been determined and the goals established, the strategies to be used to reach the goal are established. As a key stakeholder during the implementation of the projects in Kenya, the study obtained some of the challenges and solutions incurred in project planning. A common failure in many planning is that the plan is never really implemented. Instead, all focus is on writing a plan document. Another challenge is deviations from the intended plan. 
\section[{n) The Role of Project Leadership on the Implementation of Rural Electrification Project}]{n) The Role of Project Leadership on the Implementation of Rural Electrification Project}\par
The study established that all projects relevant stakeholder is provided by the projects updates information. Also, the study found that: the project manager has put in place a clear and effective communication plan with the project stakeholders'; stakeholders believe the project manager has the necessary knowledge and skills needed to attain the success of the project; and that there is the proper social interaction among stakeholders depending on their influence in the project. Furthermore, the study found that stakeholders are involved in the processes of the entire project decision making concerning appointing the project leader; the project leader has developed a Stakeholders register that shows all the project stakeholders; and that in dealing with project stakeholders' the project manager applies different leadership styles. The study findings agree with the findings of \hyperref[b35]{Muller and Turner (2007)} that the project manager's leadership competencies influenced project success. Emotional competence is a significant contributor to project success in all projects. Therefore, managerial competence is a significant contributor to some project success. It also agrees with the findings of Limsila and Ogunlana (2008) that transformational leadership was found to be the dominant style and influence a higher subordinates' commitment to giving higher leadership outcomes in terms of effectiveness, satisfaction, and extra efforts. 
\section[{o) The Moderating Role of Stakeholder Attributes on the Implementation of Rural Electrification Project}]{o) The Moderating Role of Stakeholder Attributes on the Implementation of Rural Electrification Project}\par
The study established that the interest of all key stakeholders has always been taken into consideration during the implementation of rural electrification projects in Kenya; the assessment of the proximity of all stakeholders is key to the implementation of rural electrification projects in Kenya; and that stakeholder's legitimacy has been considered during the implementation of rural electrification projects in Kenya. The study further found that stakeholders participate in key decisions of the project; and that the main objective of any project is to meet or exceed the expectations of its stakeholders due to their influence. These findings are in agreement with Duncan (2018) that stakeholders must be identified before the start of any project to allow for buy-in into project activities and its intended objectives. He added that well-aligned stakeholders will support the project activities, provide support and resources during challenging times. The finding also concurs with Alexander, (2018) that without full buy-in from key stakeholders, projects might suddenly take a sharp turn for the worst, risking the final deliverables and customer satisfaction.\par
The study also identified other stakeholder attributes that can affect project implementation.\par
Financial stakeholders, such as unions and materials suppliers, can use their influence and production to demand greater financial benefit. Contractors can negatively affect the project through time and cost overruns. When a delay is caused by a special-interest group, it can increase the cost of the project by adding the expense of legal proceedings. Political stakeholders can also use the project to ingratiate themselves to voting blocks and political donors. The study found other ways stakeholder attributes can assist during the implementation process. When stakeholders are adequately engaged, their influence spreads far and wide. They provide expertise. Stakeholders are a wealth of knowledge about current processes, historical information, and industry insight. It's important to involve all key stakeholders when gathering and documenting requirements to avoid missing major deliverables of the project. This is because stakeholders can provide requirements or constraints based on information from their industry that will be important to have when understanding project constraints and risks.  \begin{figure}[htbp]
\noindent\textbf{} \par 
\begin{longtable}{P{0.1525233644859813\textwidth}P{0.4067289719626168\textwidth}P{0.29074766355140186\textwidth}}
Year 2020\tabcellsep Project Risk Management\tabcellsep \\
58\tabcellsep ? Mitigation measures ? Stakeholders analysis\tabcellsep \\
Volume XX Issue XVII Version I\tabcellsep ? Risk registers Project Planning ? Project charter. ? Tools \& techniques ? Project management plan Project Leadership ? Communication plan\tabcellsep Project Implementation ? Meeting goals \& objectives ? Proper scheduling ? Benefit value for money ? End user satisfactions.\\
( ) A\tabcellsep ? Style ? Strategy\tabcellsep \\
Global Journal of Management and Business Research\tabcellsep ? Qualification and experience\tabcellsep Stakeholders Attributes ? interest ? proximity ? legitimacy\end{longtable} \par
  {\small\itshape [Note: © 2020 Global JournalsModerating Role of Stakeholders Attributes on Implementation of Rural Electrification Projects in Kenya]} 
\caption{\label{tab_0}}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{1} \par 
\begin{longtable}{P{0.85\textwidth}}
Project Implementation\end{longtable} \par
 
\caption{\label{tab_2}Table 1 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{2} \par 
\begin{longtable}{P{0.2833333333333333\textwidth}P{0.4407407407407407\textwidth}P{0.1259259259259259\textwidth}}
\tabcellsep Shapiro-Wilk\tabcellsep \\
Statistic\tabcellsep Df\tabcellsep Sig.\end{longtable} \par
 
\caption{\label{tab_3}Table 2 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{3} \par 
\begin{longtable}{P{0.6375\textwidth}P{0.2125\textwidth}}
Tolerance\tabcellsep VIF\end{longtable} \par
 
\caption{\label{tab_4}Table 3 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{4} \par 
\begin{longtable}{P{0.4697368421052632\textwidth}P{0.05592105263157894\textwidth}P{0.1789473684210526\textwidth}P{0.14539473684210527\textwidth}}
Ho: Constant variance\tabcellsep \tabcellsep \tabcellsep \\
Statistics\tabcellsep df\tabcellsep Stat value\tabcellsep p-value\\
Chi-squared\tabcellsep 347\tabcellsep 2.6874\tabcellsep 0.5412\end{longtable} \par
 
\caption{\label{tab_5}Table 4 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{5} \par 
\begin{longtable}{P{0.371875\textwidth}P{0.046484375\textwidth}P{0.0796875\textwidth}P{0.13945312499999998\textwidth}P{0.2125\textwidth}}
Model\tabcellsep R\tabcellsep R Square\tabcellsep Adjusted R Square\tabcellsep Std. Error of the Estimate\\
1\tabcellsep .793 a\tabcellsep .629\tabcellsep .601\tabcellsep .11517\\
\multicolumn{3}{l}{a. Predictors: (Constant), Project Risk Management}\tabcellsep \tabcellsep \end{longtable} \par
 
\caption{\label{tab_6}Table 5 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{6} \par 
\begin{longtable}{P{0.41005025125628136\textwidth}P{0.11959798994974874\textwidth}P{0.1281407035175879\textwidth}P{0.038442211055276385\textwidth}P{0.08115577889447236\textwidth}P{0.029899497487437185\textwidth}P{0.04271356783919598\textwidth}}
\tabcellsep Model\tabcellsep Sum of Squares\tabcellsep df\tabcellsep Mean Square\tabcellsep F\tabcellsep Sig.\\
\tabcellsep Regression\tabcellsep 1.79\tabcellsep 1\tabcellsep 1.79\tabcellsep 13.769\tabcellsep .000 b\\
1\tabcellsep Residual\tabcellsep 344.87\tabcellsep 345\tabcellsep 0.13\tabcellsep \\
\tabcellsep Total\tabcellsep 346.66\tabcellsep 346\tabcellsep \tabcellsep \\
\multicolumn{3}{l}{a. Dependent Variable: Project Implementation}\tabcellsep \tabcellsep \tabcellsep \\
\multicolumn{3}{l}{b. Predictors: (Constant), Project Risk Management}\tabcellsep \tabcellsep \tabcellsep \end{longtable} \par
 
\caption{\label{tab_7}Table 6 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{7} \par 
\begin{longtable}{P{0.0041871921182266006\textwidth}P{0.16330049261083743\textwidth}P{0.34753694581280786\textwidth}P{0.08793103448275862\textwidth}P{0.14236453201970442\textwidth}P{0.05024630541871921\textwidth}P{0.05443349753694582\textwidth}}
\tabcellsep Model\tabcellsep \multicolumn{2}{l}{Unstandardized Coefficients}\tabcellsep Standardized Coefficients\tabcellsep t\tabcellsep Sig.\\
\tabcellsep \tabcellsep B\tabcellsep Std. Error\tabcellsep Beta\tabcellsep \tabcellsep \\
1\tabcellsep (Constant) Project Risk Management\tabcellsep 0.670 0.646\tabcellsep 0.101 0.126\tabcellsep 0.793\tabcellsep 6.634 5.127\tabcellsep .000 .000\\
\tabcellsep \tabcellsep \multicolumn{3}{l}{a. Dependent Variable Project Implementation}\tabcellsep \tabcellsep \end{longtable} \par
 
\caption{\label{tab_8}Table 7 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{8} \par 
\begin{longtable}{P{0.34421487603305784\textwidth}P{0.049173553719008264\textwidth}P{0.08429752066115702\textwidth}P{0.1475206611570248\textwidth}P{0.22479338842975208\textwidth}}
Model\tabcellsep R\tabcellsep R Square\tabcellsep Adjusted R Square\tabcellsep Std. Error of the Estimate\\
1\tabcellsep .743 a\tabcellsep .552\tabcellsep .527\tabcellsep .22923\\
\multicolumn{3}{l}{a. Predictors: (Constant), Project Planning}\tabcellsep \tabcellsep \end{longtable} \par
 
\caption{\label{tab_9}Table 8 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{9} \par 
\begin{longtable}{P{0.38994845360824737\textwidth}P{0.122680412371134\textwidth}P{0.1402061855670103\textwidth}P{0.03943298969072165\textwidth}P{0.08762886597938144\textwidth}P{0.026288659793814433\textwidth}P{0.04381443298969072\textwidth}}
\tabcellsep Model\tabcellsep Sum of Squares\tabcellsep Df\tabcellsep Mean Square\tabcellsep F\tabcellsep Sig.\\
\tabcellsep Regression\tabcellsep 2.251\tabcellsep 1\tabcellsep 2.251\tabcellsep 4.247\tabcellsep .000 b\\
1\tabcellsep Residual\tabcellsep 182.85\tabcellsep 345\tabcellsep 0.53\tabcellsep \\
\tabcellsep Total\tabcellsep 185.101\tabcellsep 346\tabcellsep \tabcellsep \\
\multicolumn{3}{l}{a. Dependent Variable: Project Implementation}\tabcellsep \tabcellsep \tabcellsep \\
\multicolumn{3}{l}{b. Predictors: (Constant), Project Planning}\tabcellsep \tabcellsep \tabcellsep \end{longtable} \par
 
\caption{\label{tab_10}Table 9 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{10} \par 
\begin{longtable}{P{0.19948979591836735\textwidth}P{0.13877551020408163\textwidth}P{0.16479591836734692\textwidth}P{0.09107142857142857\textwidth}P{0.14311224489795918\textwidth}P{0.056377551020408166\textwidth}P{0.056377551020408166\textwidth}}
\tabcellsep \tabcellsep \multicolumn{2}{l}{Unstandardized}\tabcellsep Standardized\tabcellsep \tabcellsep \\
\tabcellsep Model\tabcellsep \multicolumn{2}{l}{Coefficients}\tabcellsep Coefficients\tabcellsep t\tabcellsep Sig.\\
\tabcellsep \tabcellsep B\tabcellsep Std. Error\tabcellsep Beta\tabcellsep \tabcellsep \\
1\tabcellsep (Constant) Project Planning\tabcellsep 1.102 0.602\tabcellsep 0.137 0.055\tabcellsep 0.743\tabcellsep 8.044 10.945\tabcellsep .000 .000\\
\multicolumn{3}{l}{a. Dependent Variable: Project Implementation}\tabcellsep \tabcellsep \tabcellsep \tabcellsep \end{longtable} \par
 
\caption{\label{tab_11}Table 10 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{11} \par 
\begin{longtable}{P{0.3524390243902439\textwidth}P{0.048373983739837395\textwidth}P{0.08292682926829269\textwidth}P{0.1451219512195122\textwidth}P{0.22113821138211384\textwidth}}
Model\tabcellsep R\tabcellsep R Square\tabcellsep Adjusted R Square\tabcellsep Std. Error of the Estimate\\
1\tabcellsep .846 a\tabcellsep .716\tabcellsep .674\tabcellsep .11803\\
\multicolumn{3}{l}{a. Predictors: (Constant), Project Leadership}\tabcellsep \tabcellsep \end{longtable} \par
 
\caption{\label{tab_12}Table 11 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{12} \par 
\begin{longtable}{P{0.39871134020618554\textwidth}P{0.122680412371134\textwidth}P{0.12706185567010309\textwidth}P{0.03943298969072165\textwidth}P{0.08762886597938144\textwidth}P{0.0306701030927835\textwidth}P{0.04381443298969072\textwidth}}
\tabcellsep Model\tabcellsep Sum of Squares\tabcellsep df\tabcellsep Mean Square\tabcellsep F\tabcellsep Sig.\\
\tabcellsep Regression\tabcellsep 1.778\tabcellsep 1\tabcellsep 1.778\tabcellsep 12.700\tabcellsep .000 b\\
1\tabcellsep Residual\tabcellsep 48.3\tabcellsep 345\tabcellsep 0.14\tabcellsep \\
\tabcellsep Total\tabcellsep 50.078\tabcellsep 346\tabcellsep \tabcellsep \\
\multicolumn{3}{l}{a. Dependent Variable: Project Implementation}\tabcellsep \tabcellsep \tabcellsep \\
\multicolumn{3}{l}{b. Predictors: (Constant), Project Leadership}\tabcellsep \tabcellsep \tabcellsep \end{longtable} \par
 
\caption{\label{tab_13}Table 12 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{13} \par 
\begin{longtable}{P{0.25362903225806455\textwidth}P{0.18850806451612903\textwidth}P{0.12681451612903227\textwidth}P{0.0719758064516129\textwidth}P{0.11310483870967741\textwidth}P{0.044556451612903225\textwidth}P{0.05141129032258065\textwidth}}
\tabcellsep \tabcellsep \multicolumn{2}{l}{Unstandardized}\tabcellsep Standardized\tabcellsep \tabcellsep \\
\tabcellsep Model\tabcellsep \multicolumn{2}{l}{Coefficients}\tabcellsep Coefficients\tabcellsep T\tabcellsep Sig.\\
\tabcellsep \tabcellsep B\tabcellsep Std. Error\tabcellsep Beta\tabcellsep \tabcellsep \\
1\tabcellsep (Constant) Project Leadership\tabcellsep 1.36 0.695\tabcellsep 0.123 0.091\tabcellsep 0.846\tabcellsep 11.057 7.637\tabcellsep .00 0 .00 0\\
\multicolumn{3}{l}{a. Dependent Variable: Project Implementation}\tabcellsep \tabcellsep \tabcellsep \tabcellsep \\
\multicolumn{2}{l}{The regression equation was:}\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \\
\tabcellsep Y = 1.360 + 0.695 X 3\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \end{longtable} \par
 
\caption{\label{tab_14}Table 13 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{14} \par 
\begin{longtable}{P{0.7013307984790874\textwidth}P{0.02100760456273764\textwidth}P{0.02585551330798479\textwidth}P{0.040399239543726234\textwidth}P{0.06140684410646387\textwidth}}
Model\tabcellsep R\tabcellsep R Square\tabcellsep Adjusted R Square\tabcellsep Std. Error of the Estimate\\
1\tabcellsep .876 a\tabcellsep .767\tabcellsep .762\tabcellsep .08495\\
2\tabcellsep .884 b\tabcellsep .781\tabcellsep .780\tabcellsep .07073\\
\multicolumn{5}{l}{a. Predictors: (Constant), Project Risk Management, Project Planning, Project Leadership, Project Monitoring, And Control}\\
\multicolumn{5}{l}{b. Predictors: (Constant), Project Risk Management, Project Planning, Project Leadership, Project Monitoring And Control,}\\
\multicolumn{5}{l}{Project Risk Management*Stakeholder Attributes, Project Planning*Stakeholder Attributes, Project Leadership*Stakeholder}\\
\multicolumn{4}{l}{Attributes, Project Monitoring, And Control*Stakeholder Attributes}\tabcellsep \end{longtable} \par
 
\caption{\label{tab_15}Table 14 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{15} \par 
\begin{longtable}{P{0.23081896551724138\textwidth}P{0.18685344827586206\textwidth}P{0.15387931034482757\textwidth}P{0.05862068965517241\textwidth}P{0.11357758620689654\textwidth}P{0.047629310344827584\textwidth}P{0.05862068965517241\textwidth}}
\tabcellsep Model\tabcellsep Sum of Squares\tabcellsep df\tabcellsep Mean Square\tabcellsep F\tabcellsep Sig.\\
\tabcellsep Regression\tabcellsep 0.436\tabcellsep 4\tabcellsep 0.109\tabcellsep 15.585\tabcellsep .000 b\\
1\tabcellsep Residual\tabcellsep 2.394\tabcellsep 342\tabcellsep 0.007\tabcellsep \\
\tabcellsep Total\tabcellsep 2.83\tabcellsep 346\tabcellsep \tabcellsep \\
\tabcellsep Regression\tabcellsep 0.704\tabcellsep 8\tabcellsep 0.088\tabcellsep 17.579\tabcellsep .000 c\\
2\tabcellsep Residual\tabcellsep 1.69\tabcellsep 338\tabcellsep 0.005\tabcellsep \\
\tabcellsep Total\tabcellsep 2.394\tabcellsep 346\tabcellsep \tabcellsep \\
\multicolumn{3}{l}{a. Dependent Variable: Project Implementation}\tabcellsep \tabcellsep \tabcellsep \\
\multicolumn{2}{l}{b. Predictors: (}\tabcellsep \tabcellsep \tabcellsep \tabcellsep \end{longtable} \par
 
\caption{\label{tab_16}Table 15 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{16} \par 
\begin{longtable}{P{0.07692307692307691\textwidth}P{0.41769230769230764\textwidth}P{0.06230769230769231\textwidth}P{0.11538461538461538\textwidth}P{0.0646153846153846\textwidth}P{0.11\textwidth}P{0.003076923076923077\textwidth}}
\tabcellsep \tabcellsep \multicolumn{2}{l}{Unstandardized}\tabcellsep Standardized\tabcellsep \\
\tabcellsep Model\tabcellsep \tabcellsep Coefficients\tabcellsep Coefficients\tabcellsep t\tabcellsep Sig.\\
\tabcellsep \tabcellsep B\tabcellsep Std. Error\tabcellsep Beta\tabcellsep \\
\tabcellsep (Constant)\tabcellsep 1.534\tabcellsep .154\tabcellsep \tabcellsep \multicolumn{2}{l}{9.961 .000}\\
\tabcellsep Project Risk Management\tabcellsep .264\tabcellsep .050\tabcellsep .237\tabcellsep \multicolumn{2}{l}{2.280 .019}\\
1\tabcellsep Project Planning\tabcellsep .258\tabcellsep .041\tabcellsep .175\tabcellsep \multicolumn{2}{l}{6.359 .000}\\
\tabcellsep Project Leadership\tabcellsep .271\tabcellsep .044\tabcellsep .195\tabcellsep \multicolumn{2}{l}{6.159 .004}\\
\tabcellsep Project Monitoring and Control\tabcellsep .774\tabcellsep .064\tabcellsep .779\tabcellsep \multicolumn{2}{l}{12.188 .000}\\
\tabcellsep (Constant)\tabcellsep 1.348\tabcellsep 0.212\tabcellsep \tabcellsep \multicolumn{2}{l}{6.358 .001}\\
\tabcellsep Project Risk Management\tabcellsep 0.346\tabcellsep 0.077\tabcellsep 1.214\tabcellsep \multicolumn{2}{l}{4.494 .040}\\
\tabcellsep Project Planning\tabcellsep 0.309\tabcellsep 0.045\tabcellsep 0.074\tabcellsep \multicolumn{2}{l}{6.867 .002}\\
\tabcellsep Project Leadership\tabcellsep 0.367\tabcellsep 0.081\tabcellsep 0.695\tabcellsep \multicolumn{2}{l}{4.531 .034}\\
\tabcellsep Project Monitoring and Control\tabcellsep 0.311\tabcellsep 0.048\tabcellsep 4.135\tabcellsep \multicolumn{2}{l}{6.479 .006}\\
2\tabcellsep Project Risk Management* Stakeholders Attributes\tabcellsep 0.259\tabcellsep 0.028\tabcellsep 0.639\tabcellsep \multicolumn{2}{l}{9.250 .000}\\
\tabcellsep Project Planning* Stakeholders Attributes\tabcellsep 0.414\tabcellsep 0.067\tabcellsep 0.008\tabcellsep \multicolumn{2}{l}{6.179 .007}\\
\tabcellsep Project Leadership* Stakeholders Attributes\tabcellsep 0.428\tabcellsep 0.078\tabcellsep 0.674\tabcellsep \multicolumn{2}{l}{5.487 .023}\\
\tabcellsep Project Monitoring and Control* Stakeholders Attributes\tabcellsep 0.885\tabcellsep 0.082\tabcellsep 1.107\tabcellsep \multicolumn{2}{l}{10.793 .000}\\
\multicolumn{2}{l}{a. Dependent Variable: Project Implementation}\tabcellsep \tabcellsep \tabcellsep \tabcellsep \\
\tabcellsep \multicolumn{2}{l}{From the findings presented in Table 16 after the}\tabcellsep \multicolumn{4}{l}{Attributes, the following moderated regression model}\\
\multicolumn{3}{l}{introduction of the moderating variable, Stakeholders}\tabcellsep was fitted;\tabcellsep \tabcellsep \\
\tabcellsep \multicolumn{6}{l}{Y=1.348+0.346X 1 +0.309 X 2 +0.364 X 3 +0.311 X 4 + 0.259 X 1 *M + 0.414 X 2 *M + 0.428 X 3 *M + 0.855X 4 *M}\end{longtable} \par
 
\caption{\label{tab_17}Table 16 :}\end{figure}
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\end{bibitemlist}
 			 		 	 
\end{document}
