Integrated Influential Factors (IIF) Model of Internal ... of variables that are causing delay in schedule time performance in construction ... Stakeholder for Projects ... the construction

Integrated Influential Factors (IIF) Model of Internal Stakeholder Causing Project

Completion Delay in Yemen Construction Industry Using AMOS-SEM Approach

Rozlin Zainal1, Najib AL-Fadhali 2, Narimah Kasim3, Norliana sarpin 4 1, 2, 3,4, ,Faculty of Technology Management and Business,

University Tun Hussein Onn Malaysia, Batu Pahat, 86400 Johor, Malaysia

Corresponding E-Mail: [email protected]

Abstract— Literature revealed that influential factors related to internal stakeholders of construction projects are capable of constituting big threat to Project completion. Hence, no effort should be considered insignificant towards curbing soaring delay in project completion. Thus, the objective of this research is to propose integrated influential factors (IIF) model as a panacea to avoid project completion delay with a view to boosting construction industries investment value. Almost one Thousand (997) sets of structured questionnaires were administered on the construction companies (owner, consultant and contractor) in Yemen out of which 283 were found usable after data screening. Purposive sampling technique was adopted while structural equation modelling (SEM) was utilized to decide the impact of internal stakeholders on Project Completion Delay (PCD). The structural model which was found to be fitted revealed a significant P-Value of the seven main hypotheses which interpreted to the fact that influential factors related tointernal stakeholders are capable of causing project completion delay. The policy implication of theresearch is to awaken government in general and ministry of work in particular from the slumber ofimplementation of construction projects responsibility to tackle time delay which in turn might be cause tocost overrun failure and abandonment.

Keyword- project management; project completion delay; stakeholder theory; IIF model, AMOS-SEM

I. INTRODUCTION

Project completion delay is a global phenomenon in the construction industry and from practice it is evident that very rarely are projects are completely finished within the approved scheduled date of completion and budgeted cost. The problem of time delay in construction projects is very dominant in both developed and developing countries, but research literature has shown that this trend occurs more in developing countries where overruns sometimes exceed 100% of the anticipated time and cost [1]. despite it, construction industry is yet encountering driving difficulties in completing the development projects according to dedicated budget, schedule date and approved technical specification [2] wherever about 50% of construction projects experienced delay[3]. Some studies in the factors affected construction projects completion studied by [4]; [5]; [6] they revealed that the factors will lead to cost overrun, claims or sometimes terminus of contracts, disputes, arbitration and litigation. The factors reported by researchers are not consistent. The inconsistency coming from the different factors they are reported, so it is critical to distinguish the variables that have more potential effects to project completion delay. [7] Pointed that 47% of construction projects in Yemen are suffering delay in schedule time and 40% of the total projects suffered cost overrun in Yemen. Research on delay on time appears to be scarce in the Yemen situation and in special amongst construction industries projects [7]; thus it is important to grasp and evaluate the causes of variables that are causing delay in schedule time performance in construction projects. However, this paper aims at proposing an integrated influential factor (IIF) model of internal stakeholder causing projects completion delay in Yemen. Related studies reveal a good number of theories that are related to completion of construction project on time. The effort is made in this section of this proposed research work to itemise applicable theories and made emphasis on the most related by justifying their relevance. Prominent among these theories include organizational theory, resource-based theory and stakeholder theory among others. The objective of this research is to propose integrated influential factors (IIF) model as a panacea to avoid delay in project completion with a view to boosting construction industries investment value.

ISSN (Print) : 2319-8613 ISSN (Online) : 0975-4024 Rozlin Zainal et al. / International Journal of Engineering and Technology (IJET)

DOI: 10.21817/ijet/2017/v9i5/170905004 Vol 9 No 5 Oct-Nov 2017 3967

II. LITERATURE REVIEW

Construction Projects in Yemen The construction industry is taken as advancements of physical training ground that convey generous as well noteworthy effects to the nation's prosperity [8]. Obviously it contributes to adverse ramifications particularly to the social physical surrounding of a nation. What's more, the industry is continually confronting incessant issues, for example, cost overrun, time delay [9], poor safety, low relevance, high consumption of resource and danger to the physical environment [10].

The construction projects In Yemen, available records showed that the construction sector of the economy represented the fourth largest employer of a workforce in the country which translated to between 9-10% of the working nationals while the average annual increase rate of the sector is almost 5.4%, effectively adding to the economic prosperity in Yemen. Considering the relatively large volume of investments presently in this sector as well as a likely increase in foreign funding from World Bank and other donor agencies for developmental projects, the request for services in this sector is evidenced to increment steadily [7]. In the real estate sector, including both commercial and residential construction, there are growing in building construction activities, especially for residential housing projects and office buildings in Sana’a and other cities. Lately, considerable top end residential and commercial complexes are under construction in Sana’a with financing by foreign investors. Currently, the investment by the government in infrastructure is almost US$ 2 billion, as comparing US$ 250 million from the donor agencies. Notwithstanding, the current output in terms of progress, quality and fund utilization is much low firstly due to lack of suitable project management, efficient supervision and monitoring and mostly relying on the contractors [7]. The kinds of projects mostly constructed in Yemen, and which are thought to be the spine of Yemen’s development endeavours, incorporated (Government buildings, commercial buildings, roads, dams, irrigation system, water purification plants, public housing, and power plants) according to study of [7]. In the mid-nineties, the economic and social circumstance in the country began to harsh prominent because of many variables yet on a very basic level because of the reunification of Yemen in May 1990[11], which caused about more difficulties in grumbling the tow different governments. A portion of the specific hardness connected with the Yemen development industry is abridged by high development cost, shaky cost, latent arranging and powerless commitment to the financial advancement as stated in study of[12]. Yemen has founded a unique building tradition, the rich, special and orderly method of the traditional Yemeni architecture and townscape is really a wonder. Until three decades ago, this culture was being perfectly preserved[13]. The real issue was and still the fast pace of changes from the old to modern and traditional building methods. Recently, this has been demonstrated that it was unlikely for the local construction sector to succeed with the enormous growth in the new forms of construction that have taken place over the past decades. 2.2 Stakeholders in the Construction Projects The idea of stakeholder theory was formally conceptualized from an academic study being undertaken in the United States in the 1960s which summarized the meaning stakeholders as those personalities with high remarkable influence in the management portfolio of an organisation that could make the business concern to stop to produce in the absence of their support, that is, the stakeholders’ support [14]. Freeman [15] in the same vein expanded this definition and refined “a stakeholder in an organization” as “any group or person who can impact or is influenced by the achievement of the organization’s set goals”. The Project Management Institute (PMI) adopted this definition and stated: “A stakeholder is an individual, group, or organization who may affect, be influenced by, or understand itself to be influenced by a decision, activity, or outcome of a project. The Project Management Body of Knowledge (PMBOK) notes that a project has many stakeholders whose targets may be related, or in conflict [16] supported that project successful completion can be basically influenced by the exercises of these two recognized groups. As stated by study of [17] stated that, the significance of stakeholders can likewise be dictated by looking at the necessities of a business and how much an association needs a particular stakeholder. In particular instances, some stakeholders can be more critical than others and the project leader should accurately analyse their needs and characteristics at various circumstances through the project life cycle phases. Depending on the association between the stakeholders and the organization, they can usually be divided into two main categories, ‘internal’ and ‘external’ [18]. Internal stakeholders are those actively engaged and formally linked to the project such as owners, consultant, contractor, subcontractor, designer, employees, and supplier. These groups in many cases are directly interested in the project and have a regular and contractual cooperation with the company. They are sometimes referred to as primary stakeholders. In the case of external stakeholders, they may not get instant responses in the organisation decision-making process, but can still affect, or be influenced, by the project [17]. The term secondary stakeholder is often adopted as a way of describing groups not directly associated with the organisation and may not be closely involved in the making of financial decision. Nevertheless, secondary stakeholders may have a significant influence on project decisions; hence their positions and postulations could be recon with in a suitable manner. Figure 1 adapted from [19] demonstrate a schematic picture of potential internal and external stakeholders.



Figure 1: Potential Stakeholder for Projects (Adapted from [19])

Successful completion of project has been broadly analysed in the construction and project management literature. Most reviews have joined on the field of project successful completion which means the way to measure the success of project and factors influencing project successful completion. [20] Express that a standout amongst the most well-known methods for measuring project successful completion is the triangle of time, cost, and required quality. Nonetheless, as indicated by the far reaching explanation by Project Management Body of Knowledge (PMBOK) Guide distributed by the Project Management Institute (PMI), project success completion standards consist of the golden triangle (time, cost, quality) and key project stakeholder’s satisfaction and their consolidation to the project [21]. Gathering the information from the literature demonstrates that time, cost, quality and stakeholder involvement have been viewed as the major success factors in construction projects.

2.3 Frameworks on project completion delay

Essentially, one of the key components revealed in the course of reviewing related literature for this thesis is the discovery of various efforts made to formulate a sustainable framework on construction project completion strategy. The researcher made a concerted effort to appraise some of these frameworks so as to build a fortified base necessary for the proposed IIF model meant for this research work. Attempting to proffer techniques to ensure project completion on dedicated time as a potent powerful technique. Several studies have identified the factors that hinder project completion. Previous studies conducted by [22], certified some of the factors that affect prevent effective Performance of Construction Sites implementation. The study was conducted in Vietnam using multiple linear regressions as the means of data analysis. Henceforth, the study also validated the dimensions and its respective indicators developed to measure the model constructs. This construct was measured using dimensions, namely management, human resources, technology, finance, material/equipment, design environment; communication project location and overtime. The study further identified factors that contribute in measuring the model construct. Moreover, the findings of the research revealed a better grasping of the multi-dimensional dimensions of the model and its concept as a latent factor. Finally, six factors were identified to be among the issues that affect performance of construction sites: management, human resources, technology, finance, material/equipment, and design. From another perspective, [23] viewed in his study a conceptual model of delay factors affecting government construction in Vietnam. The factors that causing projects completion delay generally which the study believed is the root causes of time delay which in turn lead to cost overrun, litigation, and abandonment that once these factors are properly taken care of that issue at every level would be curtailed if not completely eradicated. These factors according to the study include owner related factors, consultant related factors, contractor related factors, project conditions related factors, contract related factors, and external factors. The research made attempt to appraise relevant empirical studies that had found these factors to have a causal effect on project completion according to scheduled date, dedicated cost and according to approved technical specification. Several studies reviewed studied only two constructs from internal stakeholders (studies like [22] used material/equipment and designer only. Similarly, [24], applied only owner related factors and contractor related factors only in their study. Additionally, [23]only studied the effect of owner related factors and contractor related factors on project completion. Nonetheless, not many studies have focused on how effective project parties

Stakeholder projects

Internal Stakeholder Owner Supplier Contractor Project Management

team (Consultant) Sub-contractor Design Team

Employees

Customer

External Stakeholder Local and national authorities and

governments. Social and political organization Local communities and general public Environmentalists Funding Bodies Nearby resident Trade & Industry Social service



(internal stakeholder)’ integration can potentially impact upon project completion and prompt delivery issues globally and the developing economy in particular like Yemen. However, this is the first study that proposes integrating all the seven internal stakeholder factors. The study adapted potential stakeholder for projects proposed by[19] . The aim of integrating these factors in this study is to evaluate which factor is dominant in causing the project completion delay.

Essentially, the main thrust of this framework is that the influence of the internal stakeholder on the project completion delay. Figure 2 demonstrates the internal stakeholders which are independent variables of this research termed consultant influential factors, contractor influential factors, sub-contractor influential factors, owner influential factors, labour influential factors, designer influential factors, supplier influential factors, while project completion delay is the dependent variable. Essentially, this primary model contains seven hypotheses as shown in Figure 2. Hypothesis (H1): Contractor Influential Factors (CONIF) have a significant and direct effect on projects completion delay. Hypothesis (H2): Consultant Influential Factors (CONSIF) have substantial influence on projects completion delay. Hypothesis (H3): Sub-Contractor Influential Factors (SUBIF) have a significant and direct effect on project completion delay. Hypothesis (H4): Owner Influential Factors (OWNRIF) have a causal effect on projects completion delay. Hypothesis (H5): Labour Influential Factors (LABIF) have a substantial influence on projects completion delay. Hypothesis (H6): Designer Influential Factors (DESIF) have a substantial influence on projects completion delay. Hypothesis (H7): Supplier Influential Factors (SUPIF) have a causal effect on projects completion delay.

Figure 2: The Primary (IIF) Model

III. RESEARCH METHODOLOGY/ RESEARCH DESIGN

The research approach is purely quantitative. It involved a pilot study with the use of questionnaire instrument. It was discovered that out of 71 factors in the questionnaire survey; only 59 factors fall in the range of very significant and 12 variables were in the range of moderately significant. Subsequently, for the questionnaire survey, this study considered 59 factors that fall in the range of very significant factors only. Last questionnaire survey sets were administered among the professionals including project owners, contractors and consultant to comprehend their perception regarding level of significant of the influential factors causing project completion delay. (997) sets of structured questionnaires were administered on the construction companies (owner, consultant and contractor) in Yemen out of which 283 survived the data screening. Of these, the majority of the respondents with 43.8% belong to contractor’s organization while 37.1% and 19.1% of the respondents were from consultants’ and owners’ organizations respectively. Most of the respondents 31.1 % of respondents have experience of handling commercial construction projects, 29.7 % of respondents are occupied with construction work of Infrastructure projects, 19.8 % of respondents have experience of handling Industrial projects, and 19.4 % of respondents are occupied in construction work of Residential projects. In terms of academic ability, most of the respondents (i.e. 46.3%) have a minimum of civil engineering degree. The gathered data was then analysed with AMOS-SEM [25] software package for simulation and modelling procedure in locating the significant and dominant factors. For the purpose of questionnaire development of the research instrument, the use of five (5) point Likert scale was used. Likert scale is proposed because of the anticipated method of data analysis (that is, Structural Equation Modelling SEM) as prescribed by [26]due to the fact that most of the questions have to do with attitudinal and perception opinions of people (unobserved data) which are usually prone to error. Purposive

Project Completion Delay

CONSIF CONTIF

OWNRIF

DESIF

SUPIF SUBIF

LABIF



and systematic sampling techniques were used while structural equation modelling (SEM) was used to determine the impact of influential factors of internal stakeholder on project completion delay. The data, having passed through various screening stages which included missing data, outlier, reliability test, multicollinearity, confirmatory factor analysis (CFA) and the structural model which was found to be fitted, revealed a significant P-Value of the seven main hypotheses except two which was Labour influential factors LABIF and CONSIF which interpreted to the fact that influential factors of internal stakeholders in construction projects during construction stages are capable of causing project completion delay. The P-Value for the five main hypotheses showed less than 0.05.

IIV. DATA ANALYSIS

This study examined the assumptions of normality at univariate level, and at multivariate level. The recommendation according to [27] is that skewness and kurtosis value scores for items of measurement should be between -1 to +1 and the results for the entire items were within the acceptable range of -1 to +1, this implies that the assumption is satisfied and indicated no deviation from data normality.

Multicollinearity happens when two or more indicators in the model are associated and give repetitive data about the response. Multicollinearity was measured by variance inflation factors (VIF) and tolerance. On the off chance that VIF value exceeding 4.0, or by tolerance under 0.2 then there is an issue with multicollinearity [28]. The outcomes demonstrates that all VIF values went from 1.037 to 1.289, and tolerance values extended from 0.77to 0.965, which showed that multicollinearity was not problematic in the data analysis. Confirmatory Factor Analysis (CFA) was tested on the measurement model covering eight constructs, include: Project completion Delay (PCD) consisting of 4 factors, Consultant Influential Factors (CONSRF) consisting of 9 causes, Contractor Influential Factors (CONTIF) consisting of 9 causes, Owner Influential Factors (CONTIF) consisting of 8 causes, Designer Influential Factors (DESIF) consisting of 7 causes, Sub-contractor Influential Factors (SUBRF) consisting of 7 causes, Supplier Influential Factors (SUPIF) consisting of 7 causes, Labour Influential Factors (LABIF) of 7 causes.

4. 1 Confirmatory Factor Analysis Results

Final CFA model is depicted in Figure 3. Based on fitness indexes as shown in Table 2, the CFA model fit well. The TLI and CFI were above 0.90, and NFI, and GFI were above 0.80 the ChiSq/df < 3, and the RMSEA was below 0.08. The items used in model are indicated in Table1.

Figure 5.3: Final CFA Model



Table 1: Item definition

Item definition CONTIF DESIF

2.1 Capability of the firm’s construction team. 3.1 Frequent design changes.

2.2 Non adherence to contract agreement

3.2 Lack of communication between design team and clients in design phase.

2.3 Inadequate modern equipment with using old technology. 3.3 Lack of experience of design team in construction project. 2.4 Lack of contractor experience 3.4 Design errors made by designers. 2.5 Money cash flow during construction. 3.5 Incomplete data collection and survey before design. 2.6 Poor Planning 3.6 Misconception of owner’s requirements by design engineer. 2.7 Mistakes during constructions 3.7 Lack of adoption of standardization in design. 2.8 Poor site management and supervision. SUPIF 2.9 Poor procurement of materials 5.1 Monopoly control by particular suppliers.

OWNRIF 5.2 Poor communication between contractor and suppliers. 4.1 Inappropriate contractual procedure 5.3 Delay in manufacturing.

4.2 Slow decisions from owner

5.4 Shortages of materials.

4.3 Delay in running bill payments for the contractor 5.5 Escalation of material prices 4.4 Conflict between owners and other parties 5.6 Lack of competent supplier. 4.5 Improper Selection of contractors 5.7 Changes in Material Specification and type. 4.6 Bureaucracy in owner's organisation CONSIF 4.7 Incapable representative 7.1 Consultant architect's reluctance for change 4.8 Poor experience in construction projects 7.2 Delay in approval of shop drawings

SUBIF 7.3 Poor site management 6.1 Conflicts between sub-contractors schedule during execution of project. 7.4 Poor coordination among parties 6.2 Recurrent change of sub-contractors because of their incompetent work 7.5 Poor project management. 6.3 Incompetent subcontractors 7.6 Poor contract management 6.4 Financial difficulties of sub-contractor 7.7 Inadequate experience 6.5 Improper planning by subcontractors. 7.8 Lack of responsibility

6.6 Interference with other trades

7.9 Delay in approving major changes in the scope of work by consultant

6.7 Low Level of experience of subcontractors in construction works LABIF PCD

8.1 Shortage of technical personnel (skilled labour) Q9.1 Delay in project completion cause time overruns. 8.2 Labour strikes due to revolutions Q9.2 Delay in project completion cause cost overruns. 8.3 Low Labour productivity. Q9.3 Delay in project completion cause disputes.

8.4 Working hour’s restrictions

Q9.4 Delay in project completion cause negotiations and court cases

8.5 Absenteeism of labour 8.6 Unqualified/inadequate experienced of labours 8.7 Weak motivations.

Inspecting the results of these fitness indices for final CFA relative to the recommended values, all these fit indices for the measurement model achieved the recommended values as indicated in Table 2.

Table 2: The Fitness Indexes for All Constructs Simultaneously (Final CFA model)

Name of Index Level of Acceptance Index Value Comments Chisq/df Chisq/df ≤3 1.614 The required level is achieved TLI TLI ≥ 0.9 means satisfactory 0.905 The required level is achieved CFI CFI ≥ 0.9 means satisfactory fit. 0.912 The required level is achieved NFI NFI ≥ 0.80 suggests a good fit 0.800 The required level is achieved GFI GFI ≥ 0.80 suggests a good fit. 0.804 The required level is achieved RMSEA RMSEA ≤ 0.08 mediocre fit. 0.047 The required level is achieved

In this study, construct validity examined by analyzing both convergent validity and discriminant validity, the construct validity is scouted by examining its relationship with other constructs; both related (convergent validity) and unrelated (discriminant validity). According to [28] Average Variance Extracted (AVE) should be 0.5 or greater to suggest adequate convergent validity, and AVE estimates for two factors also should be greater than the square of the correlation between the two factors to prepare proof of discriminant validity [28]. According to[29], if the AVE is higher than the square of the correlation coefficient among the constructs, it can be asserted that discriminant validity is satisfied. In addition, in this study, the reliability assessed through internal reliability (Cronbach alpha >= 0.70), and construct reliability (CR >=0.70). Table 3 shows measures of the reliability of a measurement model, construct reliability (CR), and average variance extracted (AVE) while Table 4 demonstrated the discriminant validity.



Table 3: The Confirmatory Factor Analysis (CFA) Report Summary for All Constructs

The diagonal values (in bold) shown in Table 4 are the square root of AVE while other values are the correlation between the respective constructs. The discriminant validity is achieved when a diagonal value is higher than the values in its row and column [29].

Table 4: shows the discriminant validity.

Construct PCDF DESIF CONTIF OWNIF CONSIF SUBIF SUPIF LABIF PCDF (0.655) DESIF 0.122 (0.797) CONTIF 0.291 0.295 (0.754) OWNIF 0.271 0.098 0.218 (0.712) CONSIF 0.182 0.085 0.154 0.152 (0.744) SUBIF 0.053 0.516 0.189 0.128 0.164 (0.782) SUPIF 0.120 0.145 0.148 0.114 0.009 0.069 (0.732) LABIF 0.030 0.007 0.088 0.132 0.012 0.088 0.102 (0.710)

From the foregoing, convergent validity for all the constructs in this research satisfied the acceptable requirement. As a result of the satisfactory outcome of the research constructs reliability and validity, thus, guarantee the progression to the next stage of multivariate analysis. Therefore, next sections presented the analysis of structural equation modeling for this research.

Construct Item Factor Loadings CR (≥ 0.6) AVE ( ≥ 0.5)

CONTF

Q2.2 Q2.3 Q2.4 Q2.5 Q2.6 Q2.7 Q2.8 Q2.9

0.610 0.740 0.800 0.820 0.803 0.780 0.702 0.745

0.749

0.570

DESNF

Q3.1 Q3.2 Q3.3 Q3.4 Q3.5 Q3.6

0.868 0.860 0.850 0.853 0.630 0.693

0.826

0.636

OWNIF

Q4.1 Q4.3 Q4.4 Q4.5 Q4.6 Q4.7

0.757 0.759 0.793 0.613 0.674 0.662

0.675

0.507

SUPLIF

Q5.1 Q5.2 Q5.3 Q5.4 Q5.5 Q5.6

0.637 0.715 0.630 0.829 0.849 0.707

0.872

0.536

SUBIF

Q6.2 Q6.3 Q6.4 Q6.5 Q6.6

0.861 0.879 0.656 0.675 0.814

0.800

0.613

CONSIF

Q7.3 Q7.4 Q7.5 Q7.6 Q7.7 Q7.8 Q7.9

0.749 0.771 0.794 0.788 0.635 0.790 0.674

0.736

0.555

LABIF

Q8.1 Q8.2 Q8.3 Q8.4 Q8.5

0.659 0.639 0.753 0.757 0.721

0.713

0.505

PCDF

Q9.1 Q9.2 Q9.3

0.690 0.590 0.680

0.610

0.502



4.2 Analysis for structural equation modeling

After the unidimensionality, reliability and validity of the research constructs were ascertained, the next stage of analysis model is the entire constructs into a structural equation model using Analysis of Moment Structure (AMOS). The exogenous and endogenous variables in the research assessment framework were arranged.Thearrangement stated with the exogenous variables Consultant Influential Factors CONSIF , ContractorInfluential Factors CONTIF ,Owner Influential Factors OWRIF ,Designer Influential Factors DESIF ,Sub‐Contractor Influential Factors SUBIF , Supplier Influential Factors SUPIF and Labour InfluentialFactors LABIF andtheendogenousvariableProjectCompletionDelay PCD attheend.Theconnectionbetween each construct is linkedwith an arrow in thehypotheses’ direction as presented in Figure4.However, themodelwas used to analyse themultidirectional relationshipswithin the entire researchconstructs.

Hence, Figure 4 presented the finalmeasurementmodel for entire research constructswhichshowsperfectcompliancewiththegoodness‐of‐fitnessfortheIIFMModel.Thegoodness‐of‐fitnessforthestructural measurement models are presented in the Table 5 which showed the goodness‐of‐fitnessindexesacceptablelevelwasrealised

Figure 4: final structural measurement model for the entire research constructs and goodness-of-fitness for IIF Model.



Table 5: Goodness of Fit indexes for The Proposed Structural Model

Final structural model presenting standardized regression coefficient for the entire research constructs. The final structural measurement model provided the analysis of the causal effect (impact) for the multiple constructs in the path diagram. First and foremost, the fitness indexes for the structural model which reflect how fit is the hypothesised model with the data at hand was observed and satisfactory within the established acceptable level of fitness indexes ([26] and [28]). The standard regression weights indicated the estimate of beta coefficient which measures the impacts of the main constructs; exogenous variables (Internal Stakeholder Constructs) and endogenous variable (Project Completion Delay). The output in Figure 5.4 showed the standardized regression coefficients with its R2 equal 0.21. The Analysis Moment of Structures (AMOS) used for the structural equation modeling in this research normally produced two types of text outputs: standardized regression weights and unstandardized regression weights for the path analysis. However, the standardized regression weight is adopted to explain the relationship among the entire constructs in the research framework and subsequently for testing the hypotheses in the research as it is recommended to be better as it is easier to interpret [26]. The criteria for evaluating structural model include squared multiple correlations (R2) and path co-efficient (β) of each path. According to [30] R² of endogenous can be assessed as substantial (R² ≥0.26); moderate (R² ≥0.13); and small (R² ≥ 0.02). From figure 5.18 it is perceived that R² of the endogenous latent variable (project completion delay) is 0.21 which shows that developed model has moderate explaining power. In assessing the path co-efficient, β value of all structural paths is compared, higher the path co-efficient the significant effect on endogenous latent variable. Figure 5.4 show that CONTIF has the highest co-efficient value of 0.24. This means the CONTIF shares high value of variance with respect to project completion delay. The second major construct causing delay is OWNRIF with path co-efficient of 0.23.

Table 6: The Standardized Regression Weight and Its Significance for the Entire Path in the IIF Model.

Path Standard Beta ≤0.85 p-value Status PCD <--- CONTIF 0.240 0.002** Supported PCD <--- CONSIF 0.130 0.068 Not Supported PCD <--- OWNRIF 0.231 0.004** Supported

PCD <--- SUBIF 0.230 0.009** Supported PCD <--- DESIF 0.170 0.050* Supported PCD <--- SUPIF 0.19 0.014* Supported PCD <--- LABIF 0.040 0.575 Not Supported

Note: * p < 0.05; ** p < 0.01; *** P< 0.001; CONSIF: Consultant Influential Factors; CONTIF: Contractor Influential Factors; OWNIF: Owner Influential Factors; DESIF: Designer Influential Factors; SUBRF: Sub-contractor Influential Factors; SUPIF: Supplier Influential Factors; LABIF: Labour Influential Factors.

5. DISCUSSION ON RESEARCH FINDINGS.

The comprehensive review of literature facilitated the earlier presented hypothesised research model as shown in the figure 4. The hypothesised result in the Table 6 outlined the outcome of every respected path in the structural measurement model. Therefore, every path’s hypothesis in this research is presented accordingly in the next paragraphs

Hypothesis (H1): Contractor influential factors have a significant and direct effect on projects completion delay. Table 6 depicts the ‘results’ to test this hypothesis of the independent construct contractor influential factors on the dependent construct project completion delay and presents the pulled information of the results for the construct of contractor influential factors in this research. In the same vein, the research’s result found that contractor influential factors (β = 0.240, and p = 0.002 < 0.05) have a significant impact on projects completion delay within the Yemen construction projects. Therefore, the hypothesis is empirically supported by this research. This implies that purposeful manipulation of the tender before construction stage has a huge impact which will lead to the select inexpert contractor. The influential factors related to the contractor are significantly contributed to time delay, cost overrun and probably lead to abandoned within the Yemen construction projects. Essentially, this finding is consistent with the past research empirical studies of [32];[31];[20]; [24] in which they all tested the some factors related to contractor and its effect on project completion.

Name of Index Level of Acceptance Index Value Comments Chisq/df Chisq/df < 3 1.461 The required level is achieved

TLI TLI > 0.9 means satisfactory 0.930 The required level is achieved CFI CFI > 0.9 means satisfactory fit. 0.935 The required level is achieved NFI NFI > 0.80 suggests a good fit 0.822 The required level is achieved GFI GFI > 0.80 suggests a good fit. 0.826 The required level is achieved

RMSEA RMSEA < 0.08 mediocre fit. 0.040 The required level is achieved



Hypothesis (H2): Consultant influential factors have the substantial influence on projects completion delay. Table 6 depicts the ‘results’ of testing this hypothesis of the independent “construct consultant influential factors” on the dependent construct “project completion delay” and presents the pulled information of the results for the construct of consultant influential factors in this research. Unlike uni-variate analysis (that depends on one information to make deductions), bi-variate analysis (that depends on two information to make deduction), SEM being a multivariate analysis tool depends on three or more information to make deductions. Synthesizing this hypothesis relative to all this information required to make deductions, the results that achieved the recommended values are: Factor loading; Squared multiple correlations; Fitness indices; Correlation coefficient; Standardized beta; Average Variance Extracted (AVE); Composite Reliability (CR); Modification Index and direction of relationship. The only item that did not achieve the recommended value is significance level. Probable reasons for such maybe the study respondents were not willing to answer the questions honestly or might be the lack of experience of respondent regarding to the important rols played by consultant. Next, maybe the consultant in construction industries in Yemen doesn’t have any direct effect on project completion delay.

Hypothesis (H3): Sub- contractor influential factors have a significant and direct effect on projects completion delay. Table 6 depicts the ‘results’ to test this hypothesis of the independent construct “Sub-contractor influential factors” on the dependent construct “project completion delay” and presents the pulled information of the results for the construct of Sub-contractor influential factors in this research. In the same vein, the research’s result found that Sub- contractor influential factors (β = 0.230 and p = 0.009 < 0.05) have a significant impact on projects completion delay within the Yemen construction projects. Therefore, the hypothesis is empirically supported by this research. This implies that purposeful manipulation of the contractor to select competent subcontractor during the construction stage. The influential factors related to sub-contractor are significantly contributed to time delay, cost overrun and probably lead to abandoned within the Yemen construction projects. Essentially, this finding is consistent with the past research empirical studies of [6]; [20] in which they all tested some factors related to sub-contractor and its effect on project completion.

Hypothesis (H4): Owner influential factors have a causal effect on projects completion delay. Table 4.28 depicts the ‘results’ to test this hypothesis of the independent construct “owner influential factors” on the dependent construct “project completion delay” and presents the pulled information of the results for the construct of owner influential factors in this research. As presented in the Table 6, research outcome shows that owner influential factors construct (β = 0.230 and p = 0.004 < 0.05) is significant and have direct effect on project completion. The outcome of this research showed a strong support for hypothesis H4 as demonstrated in the final structural measurement model. By implication, therefore, the research finding showed that the owner of the construction project has a significant impact to projects completion delay. Therefore, above research hypothesis is supported. This research finding supported the past empirical outcome of[33];[34];[32];[35] who reported that some influential factors of owners has a direct negative effect on completion.

Hypothesis (H5): labour influential factors have a substantial influence on projects completion delay. Table 6 depicts the ‘results’ to test this hypothesis of the independent construct labour influential factors on the dependent construct project completion delay and presents the pulled information of the results for the construct of labour influential factors in this research. Unlike uni-variate analysis (that depends on one information to make deductions), bi-variate analysis (that depends on two information to make deduction), SEM being a multivariate analysis tool depends on three or more information to make deductions. Synthesizing this hypothesis relative to all this information required to make deductions, the results that achieved the recommended values are: Factor loading; Squared multiple correlations; Fitness indices; Correlation coefficient; Standardized beta; Average Variance Extracted (AVE); Composite Reliability (CR); Modification Index and direction of relationship. The only item that did not achieve the recommended value is significance level. It may be convenient to state that the hypothesis is supported. The result shows that labour construct factors (β = 0.040 and p = 0.575 > 0.05) is rejected to impact projects completion delay. The research outcome confirms that the influential factor related to the labour of construction project during construction stage was to be not significant in a construction project in Yemen. This may be due to the lake of awareness of study respondents towards the significance of labours in construction sectors or maybe Yemen don’t suffer from labour problem due to the large of poverty in Yemen. The labour tries to be qualified and skilled in order to overcome the difficulties face them in income. In addition, this research finding is consistent with the empirical findings by [7]; [22] in which they variously reported that factors of employee of human not directly affecting the project performance.

Hypothesis (H6): Designer influential factors have a substantial influence on projects completion delay. Table 6 depicts the ‘results’ to test this hypothesis of the independent construct “designer influential factors” on the dependent construct “project completion delay” and presents the pulled information of the results for the construct of designer influential factors in this research. The result shows that designer construct factors ((β = 0.170 and p = 0.050 = 0.05)) is significant to impact projects completion delay. Therefore, hypothesis H6 is supported. The research outcome confirms that the influential factors related to the designer of the construction



project during construction stage were to be significant in controlling, checking and even preventing time delay, cost overrun and failure of a project. This implies that from the respondent’s perspective if the government of Yemen could select proper designer companies for a development project, its positive effects would be felt in project failure prevention. In addition, this research finding is consistent with the empirical findings by [36] in which supported that influential factors of designing significantly influencing project completion.

Hypothesis (H7): Supplier influential factors have a causal effect on projects completion delay. Table 6 depicts the ‘results’ to test this hypothesis of the independent construct supplier influential factors on the dependent construct project completion delay and presents the pulled information of the results for the construct of supplier influential factors in this research. As presented in the Table 6, research outcome shows that supplier influential factors construct (β = 0.190 and p = 0.014 < 0.05) is significant and have direct effect on project completion delay. The outcome of this research showed a strong support for hypothesis H7 as demonstrated in the final structural measurement model. By implication, therefore, the research finding showed that the supplier of construction project has a significant impact to projects completion delay. Therefore, above research hypothesis is supported. This research finding supported the past empirical outcome of [37]; [38] [39] who reported that some influential factors of supplying materials has a direct negative effect on completion. In summary and by implication, influential factors related to internal Stakeholder that direct causing projects completion delay are found to be a great threat to construction project development.

4.6 Limitations of the research.

The investigation of the study was carried out under several limitations. For example, the study was limited to the construction stage of construction projects and only internal stakeholder’s categories of influential factors were included in this research. The study was limited only for human related and no discussion related to external impact on project completion delay. Furthermore, the study was carried out in the State of Sana’a only from the Yemen region. The (IIF) model is that only covers the internal stakeholder of the projects and also maybe the external stakeholder can as well affect in project completion which is suggested to be a point of research for future. This research was based on practitioners and participant’s opinions rather than actual occurrences on projects.

4.7 Conclusion

This study examined the influential factors which related to an internal stakeholder in construction projects that causing project completion delay in Yemen construction industry using AMOS -SEM technique. These factors are grouped into seven latent variables for modelling in AMOS software. The developed model was tested in two stages: the confirmatory factor analysis and structural model. It was found that the CFA all the constructs in the model are reliable and valid. For the structural model, it was found that all the constructs contributed significantly to project completion delay except LABIF and CONSIF group of factors are the least significant contributor to project completion delay. Finally, it was found that the overall model has high ability to generalize the model for nationwide representation. This paper highlighting the problem statement of this research, it was mentioned that the consequences of influential factors related to an internal stakeholder of construction projects are significantly causing delay in project completion which probably lead to failure and abandonment. From the foregoing therefore, with reference to the relationship between the objectives of this paper, the structural measurement model and the hypotheses set for this study, it could be said that as it has been proven that influential factors related to construction project are capable of influencing project completion, the study has provided proof that any effort made to avoid the influential factors related to internal stakeholder using the Integrated influential Factors Model (IIF) is a step believed to be taken in the right direction to avoid delay in project completion. From the findings and recommendations of this study, the fear of project completion delay is expected to drastically eliminated, it will raise the stakeholders’ expectations in terms of effective projects management. The findings of this study will guide construction organization in Yemen and the Middle East, particularly project managers and practitioners to abandon inappropriate control processes, and implement the better practice. It will improve and open a new area of construction management research and contribute to enhancing knowledge in the profession.

ACKNOWLEDGMENT

The research is supported by Research and Development Centre (R&D), office for Research, Innovation Commercialization an consultancy Management (ORRIC), university Tun Hussein Onn Malaysia (UTHM) for the approved fund which makes this important research viable and effective.

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