addressing crucial risk factors in the middle east construction industries

Sustainable Building Conference 2013 Coventry University

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ADDRESSING CRUCIAL RISK FACTORS IN THE MIDDLE EAST CONSTRUCTION INDUSTRIES: A COMPARATIVE STUDY OF SAUDI

ARABIA AND JORDAN

Abdullah Albogamy†, Darren Scott†, Nashwan Dawood†, Ghanim Bekr•

†Teesside University, School of Science & Engineering Teesside University, TS1 3BA, UK

e-mail: [email protected], [email protected], [email protected]

•University of Applied Science, Faculty of Engineering University of Applied Science, Amman, Jordan

e-mail: [email protected]

Abstract. Delay is a key issue in the construction industry globally and the Middle East countries are no exception. Studies of several researchers in the Middle East region have reported that 70% of all public sector construction projects fail to complete on time. This paper documents the results from an investigation into several delay factors in the Kingdom of Saudi Arabia (KSA) and Jordan. The primary data was gathered via questionnaire, by including a list of 63 crucial delay factors and asking respondents to rank each factor according to its frequency of occurrence and degree of impact. The findings are the ranking differences in each country. In addition, it is also found through critical analysis of delay factors that factors extracted using factor analysis are extremely crucial at this time and need to be addressed urgently to avoid further time overruns. The work reported in this paper is part of a PhD study which aims to outline the main causes of delay in public building projects and to develop a risk management framework to mitigate the impact of those delay factors for sustainable building construction.

Keywords causes of delay, risk management framework, Middle East

1 INTRODUCTION One of the most critical problems of construction industries in developing countries is

construction delays (Sweis et al., 2007) that often hinder sustainable construction. The key challenge for construction companies today is to complete projects on time and within the estimated budget. Over the past two decades, construction activities have increased rapidly in developing countries, particularly in the Gulf region as the governments of those countries have announced substantial spending on infrastructure improvement (Samba Financial Group, 2012). On the other hand, however, the issue of delay has created a negative image for the industry. This study aims to outline the main causes of delay in public building projects in Middle East countries with particular focus on the KSA and Jordanian construction industries. In this paper, the ranking results of the causes of delay factors in the KSA are first compared to Jordan, and then factor and correlation analysis is conducted to find the most crucial factors at this time.

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Abdullah Albogamy, Darren Scott, Nashwan Dawood and Ghanim Bekr

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2 BACKGROUND STUDIES Many researchers from different countries have found several reasons for the delays in

construction projects. For instance, Assaf et al. (1995) identified 56 key delay factors that were destroying the fabric of the construction industry in Saudi Arabia as ‘cankerworm’. They concluded that changes in design and order, payment delays, and shop drawings were the most significant contractor-related delay factors. Similarly, financing issues, conflict between contractor and consultant, slow decision making from the owner, bureaucracy issues, unskilled labour, and errors in infrastructural design were the other prominent factors that were adversely affecting the construction industry in the KSA. Another study related to Saudi Arabia identified three crucial delay factors, namely problems in obtaining work permits from government and authorities, a low-bid tendering system, and cash-flow problems (Al-Khalil and Al-Ghafly, 1999).

Faridi and El-Sayegh (2006) studied the causes of delay in the building projects of the UAE. They found that the top five critical factors causing delay were: (1) drawing preparation and approval; (2) inadequate and poor planning; (3) lack of quick decision making from the owner; (4) lack of manpower; and (5) lack of proper supervision and management. Similarly, Sweis et al. (2007) outlined five major factors causing delays in the Jordanian construction industry. They were: financial difficulties faced by the contractors; many changes in orders from the client; poor planning and scheduling by the contractor; unskilled labour; and a shortage of technical and skilled professionals.

Razek et al. (2008) from Egypt found that inadequate and improper planning, inexperienced and unskilled contractors, a lack of contract management, and payment delays were the critical delay factors. Similarly, Frimpong et al. (2003) studied the causes of delay in construction projects in Ghana and concluded that financial problems and modifications in the scope of projects were the most influencing factors causing delays. Doloi et al. (2011) outlined many factors causing delays in the Indian construction industry. The top five factors were: delays in material delivery by vendors; late availability of drawings/designs; financial constraints of the contractor; an increase in the scope of work; and obtaining permissions from local authorities. It is learned from the above studies that delay is a common problem that construction industries in the Middle Eastern countries are facing over a long period of time. Although, the causes of delay are different in each country but they ultimately result in cost and time overrun and consequently obstruct sustainable construction.

3 RESEARCH METHODOLOGY The positivism philosophical paradigm is chosen to conduct this research. Using positivism

paradigm, the researchers quantitative addressed research objectives using survey method. On the other hand, the descriptive research design is employed to explain the causes of delay and their possible impact on construction industries in Jordan and Saudi Arabia. The scope of this research paper is limited to public building projects, and a mixture of primary and secondary data is used to identify major causes of delays in the construction industries of the KSA and Jordan. A combination of qualitative and quantitative methods is adopted by looking at the nature of the study. The qualitative approach is chosen to observe the behaviour of construction participants, as well as the patterns, processes and themes of the construction process using literature review. On the contrary, the quantitative approach is employed to


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analyse the data of delay factors collected through surveys from construction participants in the KSA and Jordan.

3.1 Population The population of this study is based on construction participants (i.e. owners, contractors,

consultants and project managers) in Saudi Arabia and Jordan. Construction professionals and parties with more than 10 years’ experience were chosen through sampling method using the following formula:

S = CL2 EP (1 - EP) / CI2 (1)

Where, S = Sample size required, CL = Confidence level, EP = Estimated prevalence of malnutrition, CI = Confidence interval

3.2 Procedure The survey method was adopted to identify and inform the most critical delay factors

hindering on-time completion of construction projects in the KSA and Jordan. The questionnaire method was mainly used to record the opinions of construction participants from the KSA and Jordan against each delay factor on the basis of its degree of occurrence and impact on construction projects. Consequently, this helped the researchers to rank the delay factors. Table 1 states the number of questionnaires distributed and received.

Participants Saudi Arabia Jordan Distributed Received Distributed Received

Owner 72 38 50 32 Contractor 47 29 50 37 Consultant 63 31 50 35 Total 182 98 150 104

Table 1: Respondents profile

The respondents were asked to rank each delay factor according to its frequency of occurrence and degree of impact on projects. The data collected from the questionnaire was analysed in two ways: (1) ranking of delay factors; and (2) critical analysis of the delay factors. Many researchers (e.g. Assaf et al., 1995; Kumaraswamy and Chan, 1998; Iyer and Jha, 2005; Faridi and El-Sayegh, 2006) believe that rating factors according to their means and standard deviations is not an appropriate way to assess overall rankings because in this way the relationships between factors are not reflected. In contrast, other techniques such as weighted average and relative index are commonly used for ranking but do not take into account both the frequency and the impact of each factor. Thus, the researchers used Relative Importance Index (RII) method to rank each delay factor on the basis of its frequency of occurrence as well as the degree of impact. The detail of the formula is as follows:

Importance Index = (Freq. Index × Severity Index) / 100 (2)

Where, Freq. Index (F.I.) = Σ [c. (a/A)] × 100/5 (3)

Severity Index (S.I) = Σ [c. (a/A)] × 100/5


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‘c’ is a constant of weighting given to each response (0=unknown, 1=never, 2=low, 3=middle and 4=high), ‘a’ is the frequency of responses, and ‘A’ is the total number of responses for this research.

The delay factors were then analysed quantitatively using three statistical techniques which included factor analysis, correlation analysis and reliability analysis. The factor and correlation analyses were performed to extract the most significant factors causing delay and to find the relationship between several seemingly related and unrelated delay factors. Finally, reliability analysis was performed to cross check if the purpose of factor analysis was fulfilled and if it was measured correctly. The Cronbach’s alpha (Cα) test using SPSS was used for reliability analysis.

4 RESULTS AND DISCUSSION

4.1 Ranking of delay factors A total of 63 factors were identified from various sources and included in the

questionnaire. Respondents were asked to rank each delay factor according to its frequency of occurrence as well as the degree of impact. RII technique, which has previously been used by several researchers in the past, was used to rank delay factors. Some researchers who have used this technique to rank construction delays are Aibinu and Jagboro (2002), Assaf and Al-Hejji (2006), Sambasivan and Soon (2006), and Doloi et al. (2011). Table 2 illustrates the top 10 causes of delay according to the ranking results.

Causes of Delay Ranking KSA

Ranking Jordan

Low performance of lowest-bidder contractor in tendering system 1 1

Delay in sub-contractors’ work 2 9 Poor qualifications, skills and experience of the contractor’s technical staff 3 8

Poor planning and scheduling of the project by the contractor 4 4 Delay in progress payments by the owner 5 2 Design changes by the owner 6 3 Shortage of qualified engineers 7 10 Delay in preparation of shop drawings 8 7 Cash-flow problems faced by the contractor 9 6 Inadequate early planning of the project 10 5

Table 2: Delay Factors

4.2 Factor analysis Factor analysis is a popular multivariate analytical technique for identifying strong

relationships among variables. In this study, Exploratory Factor Analysis (EFA) was conducted because it is based on the common factor model and is useful for identifying seemingly related and unrelated factors (Doloi, 2009). The first step in EFA was to identify and display delay factors in the data matrix, which is a collection of figures arranged into one or more columns and rows (Reymont and Joreskog, 1993). At the next stage, to assess the


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sufficiency of the questionnaire data for factor analysis, the Kaiser-Meyer-Olkin (KMO) test was carried out. A KMO value near to 1 represents a strong correlation and reliability between attributes. The overall KMO value of the total of 31 extracted attributes is 0.704, which is considered ‘good’.

In this research, 31 out of 63 significant factors were extracted using the Principal Components (PC) method. PC method was preferred because it analyses all variances in the items as well as helping the researcher to minimise several correlated delay factors into a smaller number of underlying factors (Wenbin, 2008).

Factor ID Factor Description

Factor Loadin

g

Variance Explaine

d

Factor I – Material related M37 Delay in materials supply 0.769 10.58% M58 Rise in the prices of materials 0.759 M38 Material quality problems 0.741 M39 Shortage of construction material 0.540 Factor II – Project related P1 Inadequate early planning of the project 0.759 10.97% P36 Shortage of equipment availability 0.744 P53 Lack of systematic engineering method to identify the time 0.713 P15 Low performance of the lowest-bidder contractor in the

Government Tendering System 0.625

P35 Poor manpower productivity 0.606 Factor III – Contractor related CT27 Poor site management and supervision by contractor 0.762 10.92% CT25 Poor communication by contractor with parties involved in

project 0.703

CT19 Poor qualifications, skills & experience of contractor technical staff 0.687

CT32 Shortage of qualified engineers 0.661 CT18 Poor planning and scheduling of the project by the contractor 0.608 Factor IV – Owner related O9 Lack of coordination with contractors 0.682 11.65% O6 Delay in the approval of contractor submittals to the owner 0.633 O7 Changes in the scope of the project 0.632 O10 Breach or modifications of contract by owner 0.623 O13 Poor qualifications and supervision of owner’s engineer 0.614 O5 Slow decision-making process of the owner 0.609 Factor V – Consultant related CN49 Poor qualifications of supervisory staff of the consultant

engineer 0.827 10.81%

CN42 Delay in approval of shop drawings 0.806 CN43 Absence of consultant’s site staff 0.722 CN41 Inadequate qualifications of consultant to the project 0.712 Factor VI – Design related


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D45 Design errors by consultant 0.848 8.67% D44 Design changes by consultant 0.845 D51 Design errors made by designers due to unfamiliarity with

local conditions and environment 0.688

D11 Design changes by the owner 0.621 Factor VII – External related E63 External work due to public agencies 0.834 7.12% E59 Changes in Laws or regulations by Government 0.743 E55 Effect of weather conditions on construction activities 0.624

Overall KMO value = 0.704

Table 3: Factor analysis

4.3 Discussion on extracted factors 4.3.1 Factor I - ‘material-related’ indicates the issues related to materials that often

cause delays in the construction industry. In Table 2, the four most significant material-related attributes are extracted, with a total variance explained of 10.58%. The factor loadings of material-related attributes range from 0.540 to 0.769 where the values of three attributes are more than 0.7. The first and fourth attributes, i.e. ‘delay of material supply’ and ‘shortage of construction materials’, have great significance in terms of time overrun in the construction process. The second attribute ‘rise in the prices of raw materials’ may result in an increase in the cost of the whole construction project. The third attribute ‘material quality problem’ is a very serious matter for construction parties and, according to Lewry and Crewdson (1994), construction participants must not compromise on this issue. Overall, ignoring material-related factors may adversely affect the whole construction project.

4.3.2 Factor II - ‘project-related’ highlights the problems associated with different aspects and levels of a construction project. Five project-related attributes are extracted in Table 2 with an appropriate variance explained value of 10.97%. The first attribute ‘inadequate early planning of the project’, with the highest factor loading value of 0.759, is one of the vital reasons of delay which is normally ignored by the construction parties in analysing construction delays (Bramble and Callahan, 2010). ‘Shortage of equipment availability’ during construction is a situation caused due to lack of proper equipment planning at the project conception phase. The third attribute, ‘lack of systematic engineering method to identify project time’, is generally the result of an unprofessional approach and perhaps a lack of commitment from the engineer or project manager. The fourth project-related attribute, ‘low performance of the lowest-bidder contractor in tendering system’, is a very common factor causing delay in the Middle Eastern countries. Most of the public clients in developing countries prefer the lowest bidder without knowing their competencies, experience, and knowledge of project management practices and planning techniques (Agumba and Fester, 2011). Finally, the fifth attribute, ‘poor manpower productivity’, results from either a lack of on-site supervision or from employing an unskilled workforce, and affects the quality delivery of the construction project.

4.3.3 Factor III - ‘contractor-related’ shows delays caused by the contractors or sub-contractors due to a lack of skills, knowledge, experience and competencies. Table 2 illustrates five critical contractor-related delay attributes with a total variance explained value of 10.92%. The first and second attributes, ‘poor site management and supervision by the


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contractor’ and ‘poor communication by the contractor’, are interrelated with each other. The importance of supervision and communication in achieving cost and time performance in construction projects is explained by several experts (for example, Potts, 2008). In addition, due to a third problematic delay factor of ‘poor qualifications, skills and experience of the contractor’s technical staff’, the contractors either may not be able to cope with challenges or may not understand the complexity of the project, both of which often result in time overruns. A ‘shortage of qualified engineers’ is also another common delay factor in Middle Eastern countries. Many public organisations hire foreign engineers for their large construction projects due to the lack of availability of qualified engineers locally. Finally, ‘poor planning and scheduling of the project by the contractor’ can lead to improper estimations about several aspects or situations while carrying out a construction project (Agumba and Fester, 2011).

4.3.4 Factor IV - ‘owner-related’ explains 11.65% of total variance and has six underlying attributes. Owner-related issues illustrate the importance of decisions and actions taken by the owner before and during the construction period. The first attribute, ‘lack of coordination with contractors’, with the highest factor loading value of 0.682, results in failure parameters in construction projects (Doloi et al., 2011). The second attribute, ‘delay in the approval of contractor submittals’, is also another aspect of lack of coordination with contractors. The third attribute, ‘changes in the scope of the project’, is very common in the Middle East due to project managers having a lack of understanding about the scope or design of the project (Kasimu, 2012). This often causes delays due to reworking, errors, repetition of tasks, lack of motivation, and financial constraints. The fourth attribute, ‘breach or modification of contract by owner’, often refers to the selection of amateur or inexperienced contractors with inadequate skills and knowledge (Doloi et al., 2011). The fifth attribute, ‘poor qualifications and supervision of owner’s engineer’, may lead to great difficulties for the owner, as well as for other construction parties, in achieving their goals in a timely manner. Lastly, the importance of the sixth attribute, ‘slow decision-making process of the owner’, can be judged by the rankings of several researchers who placed it within the top five factors causing construction delays in developing countries.

4.3.5 Factor V - ‘consultant-related’ indicates delay problems associated with the consultants. In Table 2, four significant consultant-related attributes are extracted with a total variance explained of 10.81% of the linear component (factor). The first attribute, ‘poor qualification and supervision of staff of the consultant engineer’, can adversely affect the objectives of the client in terms of cost and time. The second attribute, ‘delay in approval of shop drawings’, usually occurs due to a lack of communication between the consultant and the approval authority. Similarly, ‘absence of consultant’s site staff’ should be monitored constantly to avoid time overruns (Assaf and Al-Hejji, 2006). Finally, the last attribute, ‘inadequate qualifications of consultant to the project’, highlights the importance of using qualified consultants so that proper project management practices and planning techniques can be employed.

4.3.6 Factor VI - ‘design-related’ highlights the importance of design-related errors and changes by the consultant and owner due to either unfamiliarity with the local environment and conditions or a lack of communication, skills, education, and experience of working with consultants. The consultant-related attributes show a total variance explained value of 8.67%.


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4.3.7 Factor VII - ‘external-related’ issues refers to work delays due to either changes in government regulations or unforeseen events such as weather or changes to the external environment. In Table 2, the total variance explained value of external-related factors is 7.12%.

4.4 Reliability of factor analysis In order to check the reliability of the factors, Cronbach’s alpha (Cα) test was performed

on each factor group to see if they were standardised. The value of Cα should be between 0 and 1 where lower values demonstrate lower internal consistency and higher values illustrate greater internal consistency. In fact, there is no set standard or pre-defined acceptable limit of Cα value. Nevertheless, the following criteria explained by Nunally (1978) for the interpretation of Cronbach’s alpha values was carefully undertaken as a rule of thumb: Cα > 0.8 ‘Excellent’; 0.8 > Cα > 0.7 ‘Good’; 0.7 > Cα > 0.5 ‘Satisfactory’; and Cα < 0.5 ‘Poor’. Table 4 shows that the value of Cronbach’s alpha (Cα) for all attributes are computed as 0.930, which is considered to be excellent’.

Factors Cronbach’s Alpha (Cα) Result Material related 0.608 Satisfactory Project related 0.602 Satisfactory Contractor related 0.755 Good Owner related 0.813 Excellent Consultant related 0.881 Excellent Design related 0.697 Satisfactory External related 0.668 Satisfactory

All Factors 0.930 Excellent Table 4: Reliability analysis

4.5 Correlation analysis In correlation analysis, correlation matrices are developed to identify the factors underlying

the attributes. For this purpose, a ‘variable reduction scheme’ was used to illustrate how different variables are grouped together and correlated with each other (Gorsuch, 1983). The Karl Pearson’s correlation coefficient ‘r’ is considered because it helps to identify linear relationships between delay factors. Table 5 shows that apart from all external-related factors and a few project-related factors, the correlation between other attributes within seven groups is statistically significant at 0.01 and 0.05 significance levels.

5 CONCLUSION Delay is the key issue that construction stakeholders in Middle Eastern countries,

particularly in the KSA and Jordan, are currently facing. This particular issue impedes sustainable building and construction in the region. Hence, this study aimed to identify causes of delay in those countries. In this regard, a survey was conducted to identify the most crucial factors causing delays in public sector projects in the KSA and Jordan. The results reveal that the top 5 factors causing delays in the KSA are: (1) Low performance of the lowest-bidder


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contractor in the tendering system; (2) delays in sub-contractors’ work; (3) poor qualifications, skills and experience of the contractor’s technical staff; (4) poor planning and scheduling of the project by the contractor; and (5) delays in progress payments by the owner. In contrast, the five most crucial factors in the Jordanian construction industry context are: (1) the low performance of the lowest-bidder contractor in the tendering system; (2) delay in progress payments by the owner; (3) design changes by the owner; (4) poor planning and scheduling of the project by the contractor; and (5) inadequate early planning of the project. It is found from the ranking and factor analysis that 31 out of 63 delay factors are extremely crucial at this time and need to be addressed urgently to avoid further time overruns in developing countries, particularly in the KSA and Jordan.

P1 P36 P53 P15 P35

P1 1 P36 .085 1 P53 -.149 -.086 1 P15 -.083 -.178 .469** 1 P35 -.123 .471** .047** -.041 1

CT27 CT25 CT19 CT32 CT18

CT27 1 CT25 .490** 1 CT19 .638** .321** 1 CT32 .192 -.012 .167 1 CT18 .672** .357** .663** .004* 1

Project-related factors Contractor-related factors

CN49 CN42 CN43 CN41 CN49 1 CN42 .606** 1 CN43 .518** .555** 1 CN41 .612** .525** 385 1

O9 O6 O7 O10 O13 O5 O9 1 O6 .350** 1 O7 .424** .463** 1 O10 .375** .331** .500** 1 O13 .268** .404** .351** .215* 1 O5 .400** .374** .224* .239* .349** 1

Consultant-related factors Owner-related factors

M37 M58 M38 M39 M37 1 M58 .548* 1 M38 .479* .278* 1 M39 .217* .010 .127 1

D45 D44 D51 D11 D45 1 D44 .696** 1 D51 .471** .423** 1 D11 .333** .437** .259** 1

E63 E59 E55 E63 1 E59 .087 1 E55 .235 .324 1

Material-related factors Design-related factors External factors

**Correlation is significant at 0.01 level (2-tailed test) *Correlation is significant at 0.05 level (2-tailed test)

Table 5: Results of correlation analysis

6 FUTURE WORK DIRECTION Despite a clear understanding of these key factors associated with the construction

industries of the KSA and Jordan, a sincere attempt could be made to address the chronic issue of time overrun by developing a risk management framework for Middle Eastern countries. In this way, the lack of construction sustainability issue can also be addressed indirectly.


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7 ACKNOWLEDGEMENT The participation, contribution and comments from the respondents are appreciated.

Furthermore, the authors are thankful to Teesside and Coventry Universities for providing research and publication facilities.

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addressing crucial risk factors in the middle east construction industries

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