An Assessment of the Factors Impacting Project Success in the Engineering Sector

Abstract

The engineering projects sector has presented numerous challenges in achieving success. The need arises to understand the reasons for these challenges and determine the best way to address the issues and achieve success using the best approach. This study aims to gain a good understanding of the factors impacting project success in the engineering sector. The literature review revealed variables that influence project success. These variables are company culture, effective management, employee engagement, and effective planning. The study presents a statistical analysis of the data. This analysis shows that each independent variable studied has a distinct impact on the dependent variable, project success. The South African engineering projects industry has shown a relationship between identified factors and project success. This study recommends laying a solid foundation to apply and improve the identified factors that have an impact on project success in the industry.

1. Introduction

There is a growing use of project management approaches in various industries and organisations [1]. Organisations accomplish their corporate goals using project management, a system used in many industries that has been shown to increase project success [1]. Research illustrates that project success is influenced by cost, time, and quality [1]. Identifying a solution and quantifying its results are necessary to optimise project work. Implementing the most suitable tools in the engineering projects industry is fundamental to project success. To deal with project and company failure in the sector, it is necessary to adopt a systematic way of working towards achieving company objectives. A project’s success in project management depends on a well-defined objective [2]. The infrastructure and project engineering sectors in South Africa are experiencing continuous difficulty in achieving success. Among the various challenges faced by project engineering companies is strong market competitiveness. Organisations in these sectors seem to find it difficult to maintain acceptable efficiency, productivity, and profitability levels during engineering projects. This hampers their ability to maximise profits and results in poor project success rates. Furthermore, organisations find it difficult to complete engineering projects within a defined project budget and schedule [3]. We see engineering projects with adverse financial outcomes [3], incomplete timeframes [4], quality issues [5], safety matters [5], etc. Several factors affect project failure [6], and various studies have been undertaken to understand the level at which each factor has an impact. This study explores the multiple factors, using them as a base to build a framework. It is deemed necessary for this research work to identify a solution and quantify its results, showing how to optimise project works. To deal with project and company failure in the sector, it is necessary to adopt a systematic way of working [4] and achieving objectives.

Companies lack integrity and systematic methods, which results in financial failure and losses. A research gap exists in addressing these problems experienced by the engineering projects sector in South Africa and providing a solution to an approach similar to that implemented in other industries, such as the manufacturing sector, which has proven successful. Unlike many other research studies conducted in the South African engineering sector, this study provides a model that looks at the holistic impact of the factors influencing project success rather than just looking at each factor independently.

This study aims to explore the factors impacting project success in the South African engineering projects industry. It seeks to identify the factors that influence project success and assess the level at which these factors are implemented in the sector. Additionally, the study aims to recommend strategies for implementing these success factors within the project engineering industry. The purpose of the study is to investigate the factors that impact the identified challenges faced in the engineering projects sector, which are, among others, the ability to maintain efficiency, productivity, and profitability.

This research will dive into numerous areas, determined by a literature review, to uncover the subtle linkages and dynamics that affect the application and effect of factors that impact project success in the South African engineering projects sector. The research provides a general framework to help organisations that want to implement project success factors and to help them decide which aspects of their systems to focus on and which to prioritise. The framework will add significant benefits to the engineering projects industry. Through the research analysis, decision-makers will better understand the factors contributing to project success in engineering projects, and the benefits of implementing them will be appreciated. Through implementation, the idea will positively contribute to projects that are difficult to control in a dynamic environment.

The success of a project depends on the operation methods followed by each department within a company. The key departments working on or contributing to a project are engineering, human resources, sales/estimating, finance, operations, commercial, and project management. Each department has a unique function and contributes to project success. Likewise, project failure depends on each department’s contribution. Overdesigned and engineering errors have financial consequences. These must be eliminated, and the engineering solution must align with practical on-site operations. For efficient operations, installation methodologies need to focus on the optimal use of internal equipment and minimise the need to fabricate custom equipment, procure extra equipment, or hire equipment from external parties. For project success, a system to achieve this alignment needs to be implemented.

2. Literature Review

The management of projects has had great success using project management techniques [1]. Several factors contribute to project failure and a lack of resources is a challenge facing engineering companies [6]. Bhika’s (2017) research on civil engineering projects assesses the problem and proposes solutions to address it [6]. Human resources are identified as a critical factor playing an essential role in a project. They are a determining factor for success or failure. Competent people must be on a project and a lack of skills is an unfortunate challenge for projects. It is necessary to have adequate skills and enough resources to cope with added responsibilities [7]. Another factor contributing to project failure is delays during a project [7]. Bhika (2107) identifies the main features that ensure a project’s success [6], as shown in Figure 1 below.

A variety of elements influence the overall performance of a project or an organisation. Technology transfer [8], leadership philosophies [9], operational skills [10], insufficient project execution expertise [11], knowledge management [12], poor health and safety effectiveness [13], the predominance of non-value-added activity [14], and collusion are some of these issues [15].

It is understood that construction in Africa has a legacy of impaired performance on projects [16]. According to the Journal of Construction Project Management and Innovation, the knowledge of lean construction in Africa (LCiA) is minimal [16]. This indicates an absence of an understanding of lean construction practises in Africa. Hence, the journal encourages using lean techniques in the African construction sector. This sector experiences many problems in Africa, some of which are highlighted below [16]:

• Construction budget overruns.
• Schedule overruns.
• Poor productivity levels.
• Safety incidents and accidents.
• Building collapses.
• Quality defects.

With the problems witnessed, the sector in Africa appears to be far behind compared to the rest of the world. Other parts of the world experience similar problems, but it is evident that Africa experiences the issues at a higher level with a more significant negative impact. It is emphasised that international construction challenges have been minimised through the implementation of lean construction. A study on operational performance used the variables of on-time supply, supply turnover, and direct workforce deployment as the three operational performance criteria to evaluate performance [17]. Poor service delivery and a depressing work atmosphere are caused by ineffective operations management [18].

2.1. Risk Management

Risk management is an essential factor that contributes to a project’s accomplishment, and the controlling of risks is strongly correlated with success and performance [19]. The ideal approach to deal with risk is to reduce project risk [20]. If risk management is not implemented correctly, there is an increased chance of project failure [19]. It is crucial to maintain a project success rate to attract foreign investors [21]. The result of underperforming projects is that investors lose confidence, and construction projects in the country see fewer investments [20]. Managing risk is essential for project success. Identifying, assessing, and monitoring risk at every phase of a project’s lifecycle is crucial. Lack of personnel competence is shown to be a factor affecting the implementation of risk management [21]. The management of risk is seen as a key feature for completing projects in the construction space [21]. It is essential to manage risks effectively for project success [20]. Poor project performance is due to dynamic construction project environments. Renault (2017) identifies some critical requirements for risk management [21], and these are stated below:

• Contractors need to have enough risk management information to foresee risks.
• Working collaboratively with the client is a way to reduce risks associated with design variations.
• Employees must receive risk management training to improve project outcomes.
• Senior management must ensure the implementation of risk management as a requirement.

The study by Renault (2017) further identifies factors affecting project completion time: variations in work issued, design changes, incomplete approvals, and substandard scheduling [21]. Risk management and its adoption play an essential role in a management structure. Newby (2016) pointed out in a survey that three-quarters of the companies studied analyse risk before avoiding it [22]. A quarter of the companies avoid risks altogether. Furthermore, it was found that only half of the surveyed companies implement risk management on projects. The ideal approach to deal with risk is to reduce project risk. It is essential to manage risks effectively for project success. Reasonable growth in risk awareness is seen in the South African construction environment. Only a small number of companies are not keeping up with the transformation [22].

2.2. Critical Success Factors

Critical success factors are the aspects of a project considered most essential to its success or failure. Projects in the construction environment face various challenges [23]. A shortage of skills and infrastructure contributes to these challenges. South Africa has a shortage of engineers, contributing to the project failure rate [23]. Risks need to be monitored, controlled, and managed. Unqualified or less qualified people are appointed in the construction sector. This is a challenge in the industry and a reason for project failure. The major components of project management techniques that can result in the success of a project are seen to be critical success factors [24]. Elements of project success are beyond the standard measures of time, budget, and scope [25]. These project-related factors [25] are presented in Figure 2 below.

The critical success factors shown in Figure 2 below have been shown to positively impact project success. Other factors identified are conflict management, quality, and project closure [25]. Another aspect affecting performance is technology transfer [8]. Research on technology transfer discovered that the technology transfer (TT) process affects project performance and may be used to gauge construction performance [8]. Leadership philosophies significantly influence project performance. It is commonly acknowledged that project managers must change their behaviour to accommodate the management requirements of various circumstances [9]. Project management (the client, engineering consultant, and construction contractor) uses many project controls to reduce subpar project performance [9].

2.3. Project Success and Failure

Many investigations have discovered that the primary causes of failure are issues outside the contractor’s or company management’s control [10]. The absence of construction performance measures is a primary cause of project failure [22]. An issue confronting the construction industry in South Africa is an absence of institutional capability in the public sector, and part of this sector is government organisation [10]. Various performance criteria and the importance level of these aspects were determined to be influential in project performance [26]. Training has been demonstrated to significantly increase project performance, among other criteria such as sustainability, job generation, and project profitability [26]. It has also been discovered that training is more commonly acquired from the top-down method and less through post-training assistance [26]. A dissertation by Mohale (2018) on the elements influencing project success emphasises the growing use of project management approaches [1]. Organisations accomplish their corporate goals in this way. Project management is used in many industries and has been shown to increase project success [1]. In Mohale’s (2018) research, the results show that project success is influenced by cost, time, and quality [1]. Project failure is less likely when these variables are balanced. The study explores what project success means and further examines the crucial elements that make a project successful. Here, infrastructure projects and the construction industry are the main topics. According to Mohale (2018), the management of projects has shown to be carried out well using project management [1]. Proper planning and managing roles are essential for project success [4]. Using a framework can significantly enhance project success [4]. Adopting a systematic methodology may deliver projects within their allocated timeframe, within budget, and accomplish the required quality output.

Ultimately, every organisation desires project success. Unsuccessful projects have numerous unintended consequences that can have a negative overall impact on a business. Financial losses are a significant source of concern. Companies must demonstrate success by completing complex projects professionally. Furthermore, cost management must be of the highest calibre, and projects must be completed within budget; all these factors are the foundation of success and can be achieved by implementing lean construction techniques.

2.4. Knowledge Acquisition

Knowledge acquisition is believed to impact administrative effectiveness in project-attentive businesses. The transient nature of work contracts can undermine employees’ loyalty to project-focused construction and engineering firms [27]. Organisations with a high knowledge-acquisition rate typically outperform the competition [27]. Furthermore, information management is crucial for improving organisational performance, as evidenced by several studies [28]. Corporate and human variables significantly influence knowledge transfer and project performance, notwithstanding the lack of information administration systems deployed in the South African construction industry [28]. In South Africa, it is unusual for construction projects to be finished with no issues, which results in scheduling issues, and high expenses that are over the budget, the absence of completion, or subpar quality [29]. This is seen as an issue predominantly for the public sector, and the result is that the building contracts at the various levels of government have regularly collapsed. It is fundamental to identify the triggers and factors that contribute to this subpar performance [29].

3. Conceptual Model and Hypotheses

The literature focuses on project success in the engineering project environment. Evidence shows that certain factors add significant value by improving project performance and success. It has been demonstrated that the South African engineering projects sector faces numerous challenges, including poor project management, low productivity, project delays, and cost overruns. The South African infrastructure and engineering projects sector, like manufacturing, can benefit from implementing certain methods. The conceptual model will cover the research gap by assessing factors affecting project success in the South African engineering projects sector. The variables were chosen by identifying critical factors in a literature review.

The conceptual model consists of independent and dependent variables. The purpose of the variables is to aid in analysing the various factors that influence the research result. The independent variable is an input variable, and in this study, it was gathered via a questionnaire. After thoroughly analysing the questionnaire responses, the independent variable affects the dependent variable. The measured dependent variable depends on the results obtained from the input or independent variable. Figure 3 below shows the conceptual model of this study.

3.1. Company Culture (CC)

The first variable identified as a factor influencing project success is the company culture. The company culture will determine the project success rate within a company. Certain companies encourage continuous improvement. To achieve project success, the correct culture is required. Management must take the proper approach to reap the most significant benefits. The company cultures explored are those with strict policies, employee-orientated, easy-going, innovative and risk-taking, team-orientated, and aggressive cultures, cultures centring integrity, and outcome-oriented cultures. The organisational culture influences employer–employee decisions. An analysis of participant feedback was performed to understand the organisational culture and its impact on project success better.

An employee-oriented culture fosters an environment where employees contribute to project success. Similarly, an innovative environment encourages employees to try new approaches, contributing positively to project success. On the other hand, a culture with strict policies that prohibit employees from completing things differently may result in project failure. Employees are restricted in many ways in this rigorous environment, which may hurt project performance because employees are limited in their ability to make changes.

3.2. Effective Management (EM)

Effective management is ultimately the key to a successful business. The management’s role is to ensure that all necessary systems are in place and that operations flow smoothly. The management team is in charge of making business decisions within an organisation. Management must take the appropriate approach when making these crucial decisions. Effective management ensures that the company’s processes and procedures carry out projects. Simultaneously, management must ensure that the business’s processes and procedures run the business. In a project environment, effective management ensures that the client’s standards and specifications carry out projects. Finally, demonstrating effective management demonstrates a commitment to ensuring client satisfaction. Management should also make sure that projects are finished within the defined schedule and budget. Effective project management ensures that material waste is kept to a minimum, that planning is current, and that quality is not compromised. Furthermore, effective management contributes to a company’s reputation for health, safety, and environmental practises. Effective management has been characterised as a critical component for the successful implementation of lean engineering techniques.

3.3. Employee Engagement (EE)

Employee engagement is a critical aspect that must be implemented in any organisation. Specific characteristics of employee engagement indicate an organisation’s likelihood for project success. Organisations should recognise the importance of their employees as they are an invaluable asset. Businesses must utilise the expertise and skills of their employees to the fullest extent possible. This can only be accomplished if an environment that encourages employee engagement exists. Employees must be given the authority to make changes in the workplace. These changes should be made to improve the work environment and achieve optimal efficiency. The individuals who carry out tasks are employees, and they possess the expertise to identify improved processes that can lead to better or more efficient outcomes. Employees must be engaged in their work because this creates an opportunity for a pool of ideas and inputs into organisational decisions. An organisation must create an environment that motivates all employees to work towards the organisation’s goals. This can only be accomplished by involving employees in various functions and decision-making. Human resources development has a critical role in this regard.

3.4. Effective Planning (EP)

The effectiveness of a company’s planning has an impact on project success. Specific characteristics indicate whether or not there is evidence of effective planning. Each of these attributes contributes something unique to the input. Evidence of project tasks being completed within the identified schedule indicates effective planning. Functions not completed within the identified schedule contribute to project failure. This is the result of poor planning. Completing project tasks on time and not deviating from the schedule is emphasised and accomplished through effective planning. This is only one variable, while other factors also contribute to effective organisational planning. Another benefit of effective planning is that equipment and materials for a project are delivered on time, eliminating the need for workers to wait for materials. Waiting for materials to arrive on a project site disrupts the sequence of events, which hurts project activity and may harm the project. Poor planning may be a contributing factor in the failure of a project in many cases. Aside from material arriving on time for a project, it is also critical that equipment and materials are correctly sorted. This would ideally be in storage areas. Items that are required must be kept, while items that are not required must be removed from the work area. On a construction site, it is critical that materials and other items are kept in a storage area and only moved to the work area when necessary. Furthermore, effective planning ensures minimal slippage of the project schedule and that projects are completed within the time frame that was initially planned. Finally, it is critical for the success of any process implementation that the organisation follows a strategic plan and uses a systematic approach to achieve set goals.

4. Methodology

The research technique includes a questionnaire-based approach that allows quantitative data to be collected from a representative sample of South African engineering experts. This study seeks to produce credible findings and valuable suggestions that will help towards project success in the South African project engineering industry.

4.1. Data Collection

The questionnaire was distributed to personnel from companies of different sizes. This included micro companies with a staff of 1 to 10 people, small companies with a staff of 11 to 50 people, medium-sized companies with a staff of 51 to 50 people, and large companies with a staff of more than 250 people.

4.2. Sampling

According to Nardi (2018), research sample criteria are characteristics used to choose participants or subjects for a research project [30]. The sample selection criteria involve selecting the industry and selecting the personnel within the sector. The research focus is on engineering projects in the mining, oil and gas, renewables, power, and built environment sectors. These companies typically include engineering projects related to mechanical and piping works, consultants offering engineering services, and specialised engineering rigging and transport services. Participants from specific departments who understand the subject matter were selected. Ideally, these personnel understood the processes and procedures implemented in the organisation. Participants in the operations and projects, senior management, and consultants were targeted. The selected participants typically had good insight into the company’s performance, procedures, and success factors during projects. The research work was restricted to companies based in South Africa. There are two reasons for the geographic restriction on the research. Firstly, a research gap on project success factors in the South African engineering projects industry has been identified. Secondly, the project was influenced by the researcher’s budget constraints.

4.3. Validity Analysis

Using IBM SPSS version 29 and JASP version 0.18.3.0 (https://jasp-stats.org) statistics software, an Exploratory Factor Analysis and a Confirmatory Factor Analysis were conducted. Bartlett’s test of sphericity and the Kaiser–Meyer–Olkin test of sampling adequacy (KMO) were conducted to check the feasibility of the analysis [31]. The factor loading was calculated to determine the allocation of an item to a specific factor [31]. A chi-square test was performed to determine the model as part of the Confirmatory Factor Analysis. The covariances were determined to understand the statistically significant relationship between individual factors and project success.

4.4. Regression Analysis

An ANOVA (Analysis of Variance) was carried out to determine the dispersion around various means [30], and linear regression analysis coefficients were analysed to understand the significance of each variable.

5. Results

5.1. Sample Size

Participants were from different sectors in the engineering project environment. The participants were from various departments, including operations, projects, and others in management roles. A total of 115 questions were distributed. Seventy-three participants returned a completed questionnaire, while the others did not respond. This is a 63% response rate. According to Nardi (2018), 20 to 30 percent of those who receive questionnaires immediately return them [30]. While receiving 50% of the surveys back in the first phase is generally seen as adequate, a lower response rate should not come as a shock [30].

5.2. Sector

The sectors targeted were engineering projects in the mining, oil and gas, renewables, and power industries, as well as engineering projects in the built environment industry. The questionnaire was distributed to personnel in these sectors. The sectors were categorised into three groups as shown in

Table 1. Number of respondents per sector.

Sector	Number of Respondents
Engineering projects in mining, oil and gas, renewables, and power industries	43
Engineering projects in the built environment industry.	24
Other	6
Total number of respondents	73

below, which displays the number of responders from each sector.

A total of 73 people participated in the questionnaire. Responses were received from 43 people working on engineering projects in the mining, oil and gas, renewables, and power sectors. Responses were received from 24 people working on engineering projects in the built environment industry. Six people responded from other sectors. Figure 4 below shows the percentage of respondents per sector.

A total of 59% of the participants were from the mining, oil and gas, renewable energy, and power engineering projects industry. The researcher had more accessible access to sectors with engineering projects in mining, oil and gas, renewables, and energy. This made it easier to distribute the questionnaire to this sector in comparison to the built environment sector, and it was also easier to follow-up on responses. In total, 33% of respondents were from engineering projects in the built environment sector, and the remaining 8% were from other sectors.

5.3. Exploratory Factor Analysis

Before conducting an Exploratory Factor Analysis (EFA), two checks need to be carried out to assess the feasibility of the analysis [31]. These tests include Bartlett’s test of sphericity and the Kaiser–Meyer–Olkin test of sampling adequacy (KMO). These tests were conducted on the independent variables, and the results are presented in

Table 2. KMO and Barlett’s test.

Kaiser–Meyer–Olkin Measure of Sampling Adequacy		0.565
Bartlett’s Test of Sphericity	Approx. Chi-Square	472.440
	df	190
	Sig.	0.000

below.

If the significance is p < 0.001, then it is appropriate to perform a factor analysis of the data [31]. Barlett’s test of sphericity for the data indicates a significance of 0.000; hence, it is appropriate to perform a factor analysis. The KMO value indicates whether it is worthwhile to conduct a factor analysis [31]. A KMO value below 0.500 is unacceptable; a value from 0.500 to 0.599 is classified as miserable [31]. A miserable KMO value is acceptable, but it indicates that the data are not robust and have a weak correlation. The KMO value of the data, as indicated in the table above, is 0.565. This is close to the lower limit of 0.500, which is miserable but acceptable. The eigenvalues were computed to assess the variance within the data. This distinction is demonstrated by a particular factor [31]. The eigenvalues of the dataset are presented in

Table 3. Eigenvalues.

Component	Initial Eigenvalues
	Total	% of Variance	Cumulative %
1	3.435	17.173	17.173
2	3.042	15.211	32.383
3	2.238	11.190	43.573
4	1.816	9.082	52.655
5	1.211	6.054	8.709
6	1.124	5.620	64.328
Extraction Method: Principal Component Analysis

below.

Factors 1 to 6 have eigenvalues greater than 1 and explain 64.328% of the variance. According to the Guttman–Kaiser rule, factors with eigenvalues greater than or equal to 1 are considered [31]. This accounts for a significant portion of the data and, given that these factors explain 64.328% of the variance, is an indication that they capture the majority of the dataset’s underlying structure. Additionally, this indicates that these factors are the most significant in explaining the relationships between the variables, and they warrant further investigation and analysis.

Table 4. Rotated component matrix.

	Component
	1	2	3	4	5	6
CC1	0.019	0.703	0.018	−0.015	0.118	0.254
CC2	0.042	−0.182	0.012	0.259	0.767	0.153
CC3	0.039	0.498	0.074	−0.020	0.680	−0.092
CC4	0.173	0.274	−0.018	−0.124	0.644	0.108
CC5	−0.121	0.558	−0.030	0.319	0.235	0.066
CC6	−0.149	0.720	−0.137	0.166	−0.140	−0.238
CC7	−0.105	0.627	−0.081	−0.002	0.216	0.393
CC8	−0.075	0.210	−0.109	0.026	0.130	0.796
EM1	0.052	0.114	0.809	−0.077	−0.131	0.054
EM2	−0.042	−0.134	0.668	0.173	−0.013	0.384
EM3	−0.144	0.028	0.651	−0.020	0.206	−0.283
EM4	−0.081	−0.219	0.760	0.028	0.027	−0.202
EE1	0.047	0.202	−0.020	0.803	−0.027	0.032
EE2	−0.022	0.216	−0.093	0.768	0.329	−0.101
EE3	−0.072	−0.118	0.132	0.783	−0.096	0.075
EP1	0.739	0.163	0.020	0.081	0.041	−0.079
EP2	0.786	−0.130	0.141	−0.017	0.049	0.047
EP3	0.772	0.013	−0.231	−0.043	0.169	0.042
EP4	0.560	−0.294	−0.265	−0.018	0.067	−0.102
EP5	0.826	−0.136	−0.009	−0.090	−0.073	−0.029
Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalisation.
Rotation converged in 8 iterations.

below provides a rotated component matrix of the data. This matrix illustrates the factor loadings, which represent the relationships between each specific factor and item within the dataset [31].

When determining the allocation of an item to a specific factor, a particular criterion is utilised. This criterion is defined by a threshold of 0.3, indicating the level of association required for an item to be linked with a factor [31]. Upon close examination of the matrix, it becomes apparent that each item is distinctly connected to a specific factor based on the established criterion. This process enables a clear and systematic approach to factor-item allocation within the matrix. The questions relating to company culture are scattered between factors 2.5 and 6. Effective management questions are related to factor 3, employee engagement is associated with factor 4, and effective planning is associated with factor 1.

5.4. Confirmatory Factor Analysis

The data were analysed using JASP to conduct Confirmatory Factor Analysis (CFA), replicating the EQS package.

Table 5. CFA chi-square test.

Model	Χ2	df	p
Baseline model	1353.419	253
Factor model	238.266	220	0.190

below is a chi-square test of the data to determine the model fit.

The p-value of the chi-square test is 0.190, which is greater than the significance level of 0.05 [30]. A p-value greater than the significance level means that we cannot reject the null hypothesis. This indicates that there is no significant difference between the observed and expected values. The non-significant p-value indicates that the model adequately fits the data, as the goodness-of-fit is assessed using the chi-square test. When the chi-square test returns a non-significant result, it means that the differences between the observed data and what the model predicts are insufficient to be considered statistically significant. Thus, the model is regarded as a good fit for the data [32]. The factor loadings of the data are shown in

Table 6. CFA fit indices.

Factor	Indicator	Estimate	Std. Error	z-Value	p
CC	CC1	0.647	0.086	7.520	<0.001
	CC2	0.340	0.112	3.031	0.002
	CC3	0.658	0.086	7.668	<0.001
	CC4	0.442	0.098	4.517	<0.001
	CC5	0.684	0.073	9.437	<0.001
	CC6	0.480	0.102	4.703	<0.001
	CC7	0.705	0.079	8.955	<0.001
	CC8	0.391	0.120	3.260	0.001
EM	EM1	0.654	0.086	7.636	<0.001
	EM2	0.557	0.108	5.149	<0.001
	EM3	0.527	0.104	5.071	<0.001
	EM4	0.808	0.119	6.805	<0.001
EE	EE1	0.754	0.116	6.501	<0.001
	EE2	0.875	0.121	7.262	<0.001
	EE3	0.491	0.102	4.839	<0.001
EP	EP1	0.598	0.082	7.279	<0.001
	EP2	0.682	0.072	9.523	<0.001
	EP3	0.763	0.063	12.079	<0.001
	EP4	0.519	0.096	5.409	<0.001
	EP5	0.861	0.052	16.443	<0.001
PS	PS1	0.652	0.087	7.528	<0.001
	PS2	0.896	0.070	12.722	<0.001
	PS3	0.752	0.083	9.067	<0.001

below.

The factor loadings from the analysis reveal that all indicators have p-values lower than 0.05, indicating that they are statistically significant. This suggests that these indicators are meaningfully associated with the underlying construct. The factor covariances are shown in

Table 7. CFA factor covariances.

	Estimate	Std. Error	z-Value	p
CC ↔ PS	0.330	0.115	2.866	0.004
EM ↔ PS	0.265	0.128	2.069	0.039
EE ↔ PS	0.297	0.120	2.470	0.014
EP ↔ PS	0.282	0.115	2.455	0.014

below.

The factor covariances suggest a statistically significant relationship between individual factors and the dependent variable, project success. The covariance between company culture and project success is shown to be statistically significant, with a p-value of 0.004. This indicates a strong relationship between the two factors, suggesting that company culture plays a significant role in determining project success. The covariance between effective management and project success is found to have a p-value of 0.039. This p-value suggests that there is a statistically significant relationship between effective management and project success. This means that there is evidence to support the idea that effective management has a notable impact on the success of a project. The covariance between employee engagement and project success was calculated to have a p-value of 0.014. This p-value suggests statistical significance, indicating that there is a meaningful and significant relationship between the factors. The p-value of 0.014 from the covariance analysis suggests a significant relationship between effective planning and project success. This indicates that there is a statistical association between effective planning and the successful outcome of projects.

5.5. Regression Analysis

ANOVA (Analysis of Variance) is especially useful in the context of this study, which has four independent variables. It allows researchers to see if there are any statistically significant differences between the means of the groups [30] defined by these independent variables. By comparing the variance within each group to the variance between groups, ANOVA can determine whether the means of the groups associated with each independent variable differ significantly from one another. This analysis determines whether the independent variables have a significant effect on the dependent variable, which is project success in this case. Understanding these distinctions reveals how each independent variable affects project outcomes. An F-value is calculated, which, if significant enough, indicates a difference between the three or more means. The F-statistic denotes the ratio. It implies that the dependent or outcome variable is influenced by the independent variable or factor [30].

Table 8. ANOVA.

Model		Sum of Squares	df	Mean Square	F	Sig.
1	Regression	11,032	4	2.758	4.635	0.002 b
	Residual	40,465	68	0.595
	Total	51,498	72

a. Dependent variable: PS. b. Predictors: (Constant), EP, EE, EM, CC.

below shows the ANOVA data.

Based on the results in the table above, the regression model is statistically significant, with a significance value of 0.002. This indicates that there are significant differences in the data, which implies the rejection of the null hypothesis. It implies a significant disparity between the means of the groups under consideration. In this situation, the independent variables exhibit a linear solid connection to the dependent variable.

Table 9. Regression coefficients.

Model		Unstandardised Coefficients		Standardised Coefficients	t	Sig.
		B	Std. Error	Beta
1	(Constant)	0.323	0.749		0.431	0.668
	CC	0.314	0.140	0.253	2.251	0.028
	EM	0.250	0.109	0.250	2.286	0.025
	EE	0.151	0.087	0.193	1.731	0.088
	EP	0.222	0.095	0.256	2.346	0.022

Dependent variable: PS.

below shows the coefficients of the independent variables and the intercept coefficient for the dependent variable.

Looking at the p-value results in the table above, three of the four independent variables are significant. Company culture, effective management, and effective planning have a p-value less than 0.05, indicating close association.

6. Discussion

The limitations and potential biases are discussed in this paragraph. The sample size of this research is limited to South Africa, so this might not be adequate to represent the continent or the world. Also, the research does not necessarily cover all provinces in South Africa, limiting the broadness of the data collected. Thus, the results are generalised to South Africa but cannot be generalised to the rest of the world. The sampling could be biassed because the sample may not cover every department in every organisation. However, the participant’s response is expected to be as accurate as possible. It also needs to be highlighted that the high non-response rate could indicate biassed findings, given the possibility that those who did not respond could have given different information from those who participated. There is a possibility that participants from the engineering projects sector might have not fully understood what is expected and might have misinterpreted the questions. This could have resulted in inaccurate participant responses, leading to unreliable data. Given the nature of the research question, ethical constraints were not a significant factor limiting the gathering of the required information. The research was designed to achieve its outcome without compromising any moral considerations.

The regression analysis from this study highlights that company culture is a significant factor, indicating its integral role in the regression model and its substantial impact on project success. This finding aligns with the existing literature, which emphasises the importance of organisational culture in project management and performance improvement. For instance, Emuze and Smallwood (2013) noted that project partners whose organisational culture is not aligned with necessary changes are more likely to resist efforts to implement performance improvements [33]. This underscores the critical role that a supportive company culture plays in facilitating successful project outcomes. Moreover, Van Der Merwe (2016) asserted that an effective company culture positively impacts operational performance, particularly when implementing lean techniques [34]. This is consistent with the findings of Ankomah et al. (2017), who emphasised that the prevailing values, norms, and practises within a company are pivotal in shaping the implementation and sustainability of lean principles across various aspects of an organisation’s operations [35]. Numerous studies have explored the adoption of lean techniques and have consistently highlighted the crucial role of company culture in successfully implementing these principles [34]. The results from this research also suggest a reduced propensity for adversarial behaviour within the workplace environment, indicating a diminished inclination towards confrontational dynamics. This finding aligns with the literature that promotes a collaborative and harmonious workplace culture as a key enabler of successful project outcomes and lean implementation.

The analysis in this study reveals that effective management is a significant determinant of project success, underscoring its vital role within the regression model. The importance of effective project management is well documented across various industries. Mohale (2018) emphasises that project management is a strategic approach widely employed to enhance success rates by efficiently coordinating resources and efforts [1]. Central to this success is the competency of project managers, whose expertise in planning, organising, and executing projects is crucial for meeting objectives on time and within budget. This aligns with the findings of this study, which highlight the critical impact of management proficiency on project outcomes. Furthermore, Dube (2019) underscores the importance of well-informed and timely decision-making in driving project success [4]. When project managers and their teams are equipped to evaluate options, anticipate outcomes, and exercise sound judgement, the likelihood of the project staying on track and achieving its objectives increases. This insight parallels the results of this study, which suggest that effective management practises, particularly those involving strategic decision-making, are key contributors to project success. The literature also highlights the influence of leadership conduct on the success of organisational change initiatives. Van Der Merwe (2016) points out that the actions of leaders are pivotal in determining the success or failure of such initiatives [34]. This study’s findings reinforce this perspective, suggesting that strong leadership and effective management practises are integral to successful project execution. Additionally, the results of this study provide important insights into current management methodologies, identifying both strengths and opportunities for improvement within the field. This aligns with broader research, which often points to the continuous need for refining management practises to adapt to evolving project demands and enhance overall success rates.

The regression analysis of this study suggests that employee engagement is not a significant factor in influencing project success within the regression model. While this result indicates that employee engagement does not have a direct impact in the context of this study, it is important to consider that further analysis may be necessary, as the existing literature consistently highlights its importance. Research by Donodofema et al. (2017) underscores the essential role of active employee involvement in diverse problem-solving processes, which is crucial for continuously enhancing an organisation’s performance [36]. This perspective is further supported by Van Der Merwe (2016), who asserts that when a company combines lean techniques with a positive company culture, it can significantly improve operational performance [34]. This often involves engaging employees in decision-making, promoting consistent leadership behaviour, and fostering accountability—all of which contribute to a successful organisational culture. Furthermore, Gewanlal and Bekker (2015) emphasise that fostering a sense of cooperation among employees is a key factor in project success [37]. Similarly, Schnetler et al. (2015) argue that the overall performance, communication, cooperation, and confidence of team members significantly impact project outcomes [38]. These insights from the literature suggest that employee engagement may indeed play a critical role in project success, even if it was not found to be significant in the regression model in this study.

The analysis in this study reveals that effective planning is a significant determinant of project success, emphasising its crucial role within the regression model. This finding aligns with the existing literature, which consistently underscores the importance of effective planning in achieving successful project outcomes. Mohale (2018) highlights that effective planning is an indispensable factor for success across various project types [1]. Thorough and strategic planning, coupled with the effective management of assigned roles and responsibilities, is essential for ensuring that projects are completed on time and within scope [4]. These elements—such as carefully outlining objectives, allocating resources, and establishing timelines—are critical in setting a strong foundation for project execution. Murwira and Bekker (2017) further emphasise that underestimating the time required to complete a project can have a detrimental effect on its success, reinforcing the need for accurate and realistic planning [11]. This is particularly important in the context of small businesses, where leaders must understand and apply strategic planning techniques to improve overall performance [39]. The findings of this study, therefore, resonate with the broader literature, highlighting that effective planning is not only significant but also a foundational element that influences the likelihood of project success. The alignment between this study’s results and the existing research reinforces the understanding that thorough and strategic planning is essential for navigating the complexities of project management and achieving successful outcomes.

The findings of this study have several practical implications that can be directly applied to enhance project success across various industries. The identified project success factors—company culture, effective management, employee engagement, and effective planning—offer valuable insights for industry professionals seeking to optimise project outcomes. For example, in the engineering sector, project managers can incorporate these factors throughout the project life cycle to improve cost management, project planning, and quality management. This practical application is likely to result in more efficient project execution and higher success rates. Moreover, this model could be adapted for use in other sectors, such as manufacturing and healthcare, where similar project dynamics exist. Organisations should consider the unique challenges and operational contexts of their specific industries when applying these findings, allowing them to develop tailored strategies that enhance project success. Another practical application of these results is their integration into training and development programmes for professionals in the engineering field. Training programmes can be customised to equip engineering project managers with the skills and knowledge necessary to implement best practises and achieve optimal project outcomes. Additionally, industry leaders can utilise these findings to establish standards and guidelines aimed at improving engineering project management practises across the sector. By doing so, they can promote effective project management practises that will enhance overall industry performance.

7. Conclusions

This study examined the elements that lead to project success. Analysing the collected data revealed how various factors contribute to project outcomes. Furthermore, the research sought to assess the factors impacting project success in the engineering projects environment. The detailed analyses of each variable, which included company culture, effective management, employee engagement, effective planning, and project success, revealed critical insights into the industry’s organisational dynamics. The Exploratory Factor Analysis indicated that company culture exhibits a scattered association between factors, while the other variables show strong associations with the factors. The Confirmatory Factor Analysis indicates that all the independent variables are strongly associated with project success. The regression analysis revealed that company culture, effective management, and effective planning are significant and, hence, have a strong association with project success. The findings are anticipated to be helpful to academics and professionals working in these fields. This study’s findings have a number of ramifications for scholars and professionals. The study provides valuable guidance to industry professionals in the engineering projects sector by identifying key factors influencing project success and making practical recommendations. Professionals can use these insights to improve project outcomes, increase efficiency, and reduce organisational risks. While the study shed light on essential aspects of project success, there is still room for more research to improve the understanding of the subject. Future research can offer valuable insights to practitioners and advance knowledge in the field by tracking progress, identifying trends, and investigating organisational dynamics over time.

Future research could explore the applicability of the identified project success factors across various industries and organisational contexts. For instance, investigating the impact of these factors on project success in sectors such as manufacturing, construction, or healthcare could reveal whether the model is specific to engineering projects or has universal applicability across different sectors. The unique environment, work methods, procedures, and challenges inherent to each industry might influence project success, indicating that the factors may impact outcomes differently depending on the sector. Additionally, it is recommended that further studies are conducted within the same industry but with a focus on different organisational characteristics, such as comparing the effects of project success factors in flat versus hierarchical organisational structures or in small businesses versus large corporations. These variations in organisational dynamics could significantly affect the relationship between the independent variables (project success factors) and the dependent variable (project success), providing insight into whether the model holds consistently across different organisational settings. Moreover, since this research was limited to organisations based in South Africa, expanding future studies to include different geographical regions would be valuable. Cultural and regional differences could influence management behaviour and practises, potentially impacting the relevance and effectiveness of the identified project success factors. By examining these factors in a broader or different geographical context, researchers can assess the model’s generalisability beyond the initial study area. Lastly, it would be beneficial for future research to include qualitative case studies within the industry. Such studies could provide a more comprehensive understanding of the findings and potentially uncover aspects of the variables that were not evident in this research. Through case studies, researchers might identify additional factors contributing to project success, offering a deeper, context-specific perspective.