Factors Affecting Accuracy of Pretender Cost Estimate

International Journal of Applied Engineering Research ISSN 0973-4562 Volume 9, Number 1 (2014) pp. 21-36 © Research India Publications http://www.ripublication.com

Factors Affecting Accuracy of Pretender Cost Estimate: Studies of Saudi Arabia Ibrahim Mahamid1*, A. Al-Ghonamy1, M. Aichouni1 1

Mohamed Binladen Research Chair on Quality and Productivity Improvement in the Construction Industry, College of Engineering, University of Hail, Saudi Arabia. * Correspondence author: Email: [email protected] Abstract Cost estimation of construction projects with high accuracy at the early phase of project development is crucial for planning and feasibility studies. Construction clients require early and accurate cost advice prior to site acquisition and commitment to build in order to enable them to take a right decision regarding the feasibility of proposed project. However, a number of difficulties arise when conducting cost estimation during the early phase. This study is conducted to identify the main factors affecting accuracy of pretender cost estimate in building construction projects in Saudi Arabia from owners’ perspective. 44 factors affecting pretender cost estimate were identified through literature review and discussion with some construction experts. The factors were tabulated in a questionnaire form and a field survey included 32 owners was performed. The results show that the top important factors affecting pretender cost estimate accuracy are: level of competitors in the tendering, material price changes, communications with suppliers, communications with client, and estimating method used. On the other hand, results indicate that timing of advertisement (weather effects), site conditions (topography, access,..etc), equipment costs, material shortage, and type of project (residential, commercial, industrial,….etc) were the lowest factors affecting accuracy of pretender cost estimate. Key words: Cost estimate, Accuracy, Pretender, Estimating, Saudi Arabia.

Introduction Cost estimating is the process of accumulating, calculating and analyzing all the cost details. In almost all contract types, the preparation of an accurate cost estimate is an essential part of any construction operation. Cost estimation of construction projects

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Ibrahim Mahamid et al

with high accuracy at the early phase of project development is crucial for planning and feasibility studies. Construction clients require early and accurate cost advice prior to site acquisition and commitment to build in order to enable them to take a right decision regarding the feasibility of proposed project. However, a number of difficulties arise when conducting cost estimation during the early phase such as lack of preliminary information, lack of database of works costs, lack of appropriate cost estimation methods, and the involvement of many environmental, political, social and external uncertainties. As a result, the construction of projects faces challenges affecting the cost estimating accuracy. Pretender cost estimate is an important issue to the construction industry. Investigation into this issue is needed to better manage cost deviation situations and to mitigate their consequences such as delay, disputation, cost overrun, delay and failure. It also provides insights for planning and taking risks into consideration in early phases of a project. Identifying factors that affecting the accuracy of pretender cost estimating and assessing their importance. This study aims at identifying the factors affecting pretender cost estimate accuracy in building construction projects in Saudi Arabia from owners’ viewpoint. To do so, 32 owners completed a structured questionnaire survey and the factors were ranked according to their level of importance. 44 factors were identified through detailed literature review and interviews involving some local construction experts. It is hoped that the research findings will assist in improving the predictive ability of the cost estimate by exploring the affecting factors of estimate accuracy.

Literature review Many studies were conducted to investigate the accuracy of cost estimating in construction projects. Odeck (2004) investigated the statistical relationship between actual and estimated costs of road construction using data from Norwegian road construction over the years 1992-1995. The findings reveal a discrepancy between estimated and actual costs, with a mean cost overrun of 7.9% ranging from -59% to +183%. Mahamid and Bruland (2012) conducted a study to investigate the statistical relationship between actual and estimated cost of road construction projects using data from Palestinian road construction projects awarded over the years 2004 to 2008. The study was based on a sample of 169 road construction projects. The findings reveal that 100% of projects suffer from cost diverge. They found that the discrepancy between estimated and actual cost has average of 14.56%, ranging from -39.3% to 98%. Flyvbjerg et al. (2003) conducted a study of 258 transportation infrastructure projects. The distribution of the 258 projects on the three types of project was as follows: rail: 58, fixed link (bridges and tunnels): 33, and road: 167 projects. The projects were located in 20 nations on 5 continents, including both developed and developing nations. The geographical distribution of projects was: Europe: 181, North America: 61, and other: 16 projects. The main findings from the study are the followings: (1) 9 out of 10 transport infrastructure projects fall victim to cost escalation, (2) For all project types: the average cost escalation is 28%, (3) Cost escalation exists across 20 nations and 5 continents; it appears to be a global

Factors Affecting Accuracy of Pretender Cost Estimate

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phenomenon, (4) Cost escalation appears to be more pronounced in developing nations than in North America and Europe, (5) Cost escalation has not decreased over the past 70 years. Al-Zarooni and Abdou (2000) conducted a survey to investigate variations in UAE building projects' estimates. They found that the variations between feasibility and contract cost, ranging between -28.5% and +36%. They stated that these variations are due to budgeting using a Single Unit Estimating basis. AlMomani (1996) conducted a study of construction cost prediction for building school buildings in Jordan. The study conduct a data of 125 school projects carried out in Jordan for the period 1984 - 1994. The results indicated that the actual cost exceeds the original contract price by 30%. Mahamid (2013) conducted a study to identify the factors affecting cost estimating accuracy in building construction projects in Palestine. He concluded that the top five affecting factors are: fluctuation in currency exchange rate, project financing, contract management, level of competitors, and cost of materials. Azhar et al. (2008) conducted a study to identify the major factors affecting cost estimating accuracy in the construction sector of Pakistan. 42 factors were short-listed to be made part of the survey questionnaire and the survey was conducted with representatives from local general contracting firms. They found that the top ten affecting factors are: fluctuation in prices of raw materials, unstable cost of manufactured materials, high cost of machineries, lowest bidding procurement procedures, poor project (site) management or poor cost control, delays between design and procurement phases, incorrect or inappropriate methods of cost estimation, additional work, improper planning, and unsupportive government policies. Koushki et al. (2005) conducted a study in Kuwait to study the factors affecting cost estimating in construction projects. A person-interview survey of 450 randomly selected private residential project owners and developers have been done. They found that the main factors affecting are: contractor-related problems, material-related problems and owners’ financial constraints. Oberlender and Trost (2003) conducted a study of 67 process industry construction projects around the world. They identified 45 factors contributing to the accuracy of early stage estimates. They summarized the factors into 11 orthogonal elements. Of the 11 factors, the five most important include: process design, team experience and cost information, time allowed to prepare estimates, site requirements, and bidding and labor climate. Odusami and Onukwube (2008) studied the factors that influence the accuracy of consultant pre-tender cost estimate in Nigeria. Data were collected, through the administration of questionnaire, from 50 randomly selected quantity surveyors in consulting firms. They concluded that the main affecting factors are: expertise of consultants, quality of information and flow requirements, project team’s experience of the construction type, tender period and market condition, extent of completion of pre-contract design, complexity of design and construction, availability and supplies of labor and materials. Shash and Ibrahim (2005) investigated the early cost estimating techniques and the procedures adopted by consulting firms in Saudi Arabia. These were achieved through the administration of a structured questionnaire. 19 consulting firms, practicing in the Eastern Province of Saudi Arabia, participated in the survey. The participating consulting firms were

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asked to assess the importance of many factors potentially affecting their decision in selecting an early cost estimating technique. They concluded that the top affecting factors are: size of the project, information available, client, project type, and time available. Abdal-Hadi (2010) conducted a study to identify the main factors affecting accuracy of pretender cost estimate in Gaza Strip. The results of analyzing 64 factors considered in a questionnaire concluded that the main factors affecting accuracy of pre-tender cost estimate are: material (prices /availability /supply /quality /imports ), closure and blockade, project team's experience in the construction type, the experience and skill level of the consultant, clear and detail drawings and specifications, quality of information and flow requirements, completeness of cost information, accuracy and reliability of cost information, currency exchange fluctuation, and finally clear contract conditions.

Research methodology The methodology of the study is as follows: 1. Fourty four (44) factors that might affect accuracy of pretender cost estimate in building construction projects were identified through literature review and discussion with some construction experts. The similar factors were grouped under one main group; the factors were divided into 6 groups: client related factors, consultants and design related factors, contract and tendering related factors, project characteristics related factors, cost estimating related factors, and resources (labors, materials, equipments) related factors. The factors were tabulated in a questionnaire form as listed in Table 1. 2. Questionnaire consisting of two parts I and II was developed. In Part I personal Information of the respondent (for e.g. work experience, organization, annual volume of construction work) was asked. Part II was aimed to obtain information about factors affecting pretender cost estimate. Respondents were asked to rate the extent to which the various factors influenced the accuracy of pretender cost estimate on a five-point Likert scale. The respondent has to choose one of the categories very high, high, moderate, low and very low (on 5 to 1 point scale). 3. A survey was conducted through emails and personal interviews in which respondents were asked to rank and score these factors according to their experience. Fourty (40) owners were approached for these surveys out of which thirty two (32) responses were received with the response rate of 80%. 4. The information collected from the questionnaire survey is analyzed statistically by using Excel statistical tools. The statistical methods that used for calculating and presenting the survey results are: Importance index: Eq. (1) Importance Index (IMP.I) (%) = ∑ a (n/N)∗100/5 Where; a is the constant expressing weighting given to each response (ranges from 1 for very low up to 5 for very high) n is the frequency of the responses


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N is total number of responses The group index was calculated by using the average of the severity indexes of the factors under each group. Statistical analysis Some statistical techniques are used to interpret the dispersion, compactness, and the degree of homogeneity of the responses for the influence of the identified 44 factors on pretender cost estimate as assessed by the owners. These techniques include computation of the weighted mean, standard deviation, and coefficient of variation. Analysis is discussed in detail in the following section, on the basis of which recommendations to construction industry of Saudi Arabia were made. Table 1: List of factors affecting pretender cost estimate accuracy and their related groups Group 1) Factors related to clients

Factors under group Financial conditions of the client Client's evaluation and awarding policy Communication and coordination with consultants Client experience in construction projects Clear scope definition for the client 2) Factors related to consultants Communications with suppliers and design Communications with client Designer's experience level The experience and skill level of the consultant Clear and detail drawings and specifications Communications and coordination between designers Volume of consultant's workload during estimation 3)Factors related to cost Estimator's experience estimating Estimating method used Time allowed for preparing the cost estimate Procedure for updating cost information Completeness of cost information Availability of data base of bids on similar project (Historical cost data) Accuracy and reliability of cost information 4) Factors related to project Project size characteristics Site conditions (topography, access,..etc) Type of project (residential, commercial, industrial,….etc) Location of project Construction techniques requirements 5) Factors related to contract and Clear contract conditions tendering Tender selection method (open, selected, negotiation, ..etc.) Method of procurement (traditional, design bid build, design and build, project management, etc) Type of contract Level of competitors in the tendering


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The taxes and other financial requirements on tender Number of competitors in the market Advanced payment Timing of advertisement ( weather effects) 6) Factors related to labors, Material price changes material and equipments Labor productivity Equipment productivity Material storage Labor costs Labor availability Equipment costs Equipment conditions Equipment availability Material shortage

4. Results and discussion 4.1 Ranking of factors The factors under each group are ranked by the measurement of importance index according to Equation (1). 4.1.1 Factors related to clients Table 2 shows the importance index and ranking of each factor under the clients group from owners’ view. 5 factors are considered under this group. The table shows that the owners pointed out “client’s evaluation and awarding policy” factor as the top affecting factor under this group with an importance value of 68.55. This result is supported by Azhar et al. (2008), who confirmed that awarding policy affects accuracy of cost estimating. “Communication and coordination with consultant” was ranked in position 2 with importance index value of 66.98. “Clear scope definition for the client” was ranked in position 3 with importance index value of 65.62. It can be noticed that all factors under this group have importance index higher than 60, indicating that all of them are highly affecting the accuracy of pretender cost estimate. Table 2: Ranking of clients’ related factors Factor

Owners' view IMP.I (%) Rank Client's evaluation and awarding policy 68.55 1 Communication and coordination with consultants 66.98 2 Clear scope definition for the client 65.62 3 Financial conditions of the client 64.79 4 Client experience in construction projects 63.13 5


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4.1.2 Factors related to consultants and design Table 3 illustrates the ranking of the 7 factors in the group related to consultants and design. The results show that the most important factor affecting the pretender cost estimate is communication with suppliers, followed by communication with clients, designer’s experience level, the experience and skill level of the consultant, clear and detail drawings and specifications, communications and coordination between designers, and volume of consultant’s workload during estimation. The surveyed owners ranked “communications with suppliers” in the first position, with an importance index value of 76.76. This factor was also ranked in the third position among all 44 factors, negatively affecting pretender cost estimate accuracy (Table 8), which indicates that communication with suppliers has a very high effect on estimate accuracy. This result is justified, as communication with suppliers keep the consultant updated with new prices, products and construction technologies. “Communication with clients” had a high effect on accuracy of pretender cost estimate, and was ranked in the second position in the consultants and design group, with an importance index value of 73.31. “Communication with clients” also ranked fourth among all 44 factors negatively affecting accuracy of pretender cost estimate (Table 8). Table 3: Ranking of Factors related to consultants and design Factor

Owners' view IMP.I (%) Rank Communications with suppliers 76.76 1 Communications with client 73.31 2 Designer's experience level 63.37 3 The experience and skill level of the consultant 61.89 4 Clear and detail drawings and specifications 58.04 5 Communications and coordination between designers 57.19 6 Volume of consultant's workload during estimation 55.76 7

4.1.3 Factors related to cost estimating Table 4 indicates the ranking of 7 factors under the group related to cost estimating. These factors were placed in descending order according to their importance: estimating method used, estimator's experience, time allowed for preparing the cost estimate, availability of data base of bids on similar project (Historical cost data), procedure for updating cost information, accuracy and reliability of cost information, and completeness of cost information. Results demonstrate that estimating method used has a high effect on accuracy of pretender cost estimate (IMP.I = 73.23), and ranked in position 5 of all 44 factors negatively affecting accuracy of pretender cost estimate. This result is justified, as the early estimates are usually budgeted using a Single Unit Estimating (cost per square meter) basis, regardless of the nature of projects and their associated risks or the construction complexity of each building type. This result is supported by Azhar et al. (2008), who confirmed that wronge


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estimating method affects accuracy of cost estimating. “Estimator's experience” had a high effect on accuracy of pretender cost estimate, and was ranked in the second position in the cost estimating group, with an importance index value of 72.10. “Estimator's experience” also ranked in the eighth position among all 44 factors negatively affecting accuracy of pretender cost estimate (Table 8). . Table 4: Ranking of Factors related to cost estimating Factor

Owners' view IMP.I (%) Rank Estimating method used 73.23 1 Estimator's experience 72.10 2 Time allowed for preparing the cost estimate 68.19 3 Availability of data base of bids on similar project 64.19 5 (Historical cost data) Procedure for updating cost information 62.66 4 Accuracy and reliability of cost information 62.50 6 Completeness of cost information 58.08 7

4.1.4 Factors related to contract and tendering Table 5 shows the importance index and ranking of each factor under contract and tendering group from owners’ view. 9 factors are considered under this group. The table shows that the top three factors affecting accuracy of pretender cost estimate are: level of competitors in the tendering, clear contract conditions, and tender selection method (open, selected, negotiation, ..etc.). Results demonstrate that “level of competitors in the tendering” has a high effect on accuracy of pretender cost estimate (IMP.I = 79.90), and ranked in position 1 of all 44 factors negatively affecting accuracy of pretender cost estimate. This result is justified, as the high level of competitor in the tendering positively affect the performance of the construction project. Such that high level competitor, in general, is financially sound with high experience in the field and highly skilled staff that help to execute the project with less cost deviations. This result is supported by Mahamid (2013), who confirmed that level of competitors affects accuracy of cost estimating. “Clear contract conditions” had a high effect on accuracy of pretender cost estimate, and was ranked in the second position in the contract and tendering group, with an importance index value of 72.33. “Clear contract conditions” also ranked in the seventh position among all 44 factors affecting accuracy of pretender cost estimate (Table 8). Tender selection method (open, selected, negotiation, ..etc.) was ranked in third position under this group and ninth among all 44 factors affecting accuracy of pretender cost estimate (Table 8). It can be seen that the top three affecting factors under this group are among top ten factors affecting accuracy of pretender cost estimate (Table 8).


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Table 5: Ranking of Factors related to contract and tendering Factor

Owners' view IMP.I (%) Rank Level of competitors in the tendering 79.90 1 Clear contract conditions 72.33 2 Tender selection method (open, selected, negotiation, ..etc.) 70.13 3 Method of procurement (traditional, design bid build, design 68.13 4 and build, project management, etc) Type of contract 64.48 5 The taxes and other financial requirements on tender 63.20 6 Advanced payment 59.57 7 Number of competitors in the market 57.65 8 Timing of advertisement ( weather effects) 52.08 9

4.1.5 Factors related to project characteristics Table 6 shows the 6 factors in the group related to project characteristics; these were ranked according to their importance in affecting accuracy of pretender cost estimate as follows: project size was ranked first; project duration was ranked second; location of project was ranked third; construction techniques requirements was ranked fourth; site conditions ( topography, access,..etc) was ranked fifth; and type of project (residential, commercial, industrial,….etc) was ranked sixth. Results demonstrate that “project size” has a high negative impact on accuracy of pretender cost estimate. This result is acceptable, as large projects faces unexpected variables that affect the accuracy of cost estimate such as poor resource management, poor site management, poor productivity, poor quality...etc. This result is supported by Shash and Ibrahim (2005), who found that project size affects accuracy of cost estimating. Results also show that “project duration” had a high negative impact on accuracy of pretender cost estimate with importance index value of 62.60. It can be noticed that none of the listed factors under this group among the top ten factors affecting accuracy of pretender cost estimate (Table 8). Table 6: Ranking of Factors related to project characteristics Factor

Owners' view IMP.I (%) Rank Project size 66.63 1 Project duration 62.60 2 Location of project 57.55 3 Construction techniques requirements 53.51 4 Site conditions ( topography, access,..etc) 52.05 5 Type of project (residential, commercial, industrial,….etc) 46.44 6


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4.1.6 Factors related to labors, materials and equipments The result in Table 7 depicts that the 10 factors under the resource (labours, materials and equipments) group have been placed in descending order as follows: material price changes, labor productivity, material storage, equipment productivity, equipment availability, labor costs, labor availability, equipment conditions, equipment costs, and material shortage. “Material price changes” have a high impact on pretender cost estimate, and ranked in position 2 of 44 factors affecting accuracy of pretender cost estimate. This result is justified, as material price is highly affected by market conditions such as supply, demand, availability, quality, national and international economics, exchange rate fluctuation, ..etc. Consequently, it affects the accuracy of pretender cost estimate. This result is supported by Mahamid (2013), Azhar et al. (2008), and Abdal-Hadi (2010). “Labor productivity” had a high effect on accuracy of pretender cost estimate, and was ranked in the second position in this group, with an importance index value of 72.81. “Labor productivity” also ranked in the sixth position among all 44 factors affecting accuracy of pretender cost estimate (Table 8). This result is acceptable, as labor productivity plays a key role in determining the financial success of a project. Table 7: Ranking of Factors related to labors, materials and equipments Factors

Owners' view IMP.I (%) Rank Material price changes 78.63 1 Labor productivity 72.81 2 Material storage 66.34 3 Equipment productivity 63.23 4 Equipment availability 61.22 5 Labor costs 60.76 6 Labor availability 58.48 7 Equipment conditions 56.16 8 Equipment costs 51.87 9 Material shortage 49.28 10

4.1.7 Overall ranks of all factors affecting accuracy of pretender cost estimate The results in Table 8 depict that the most 5 important factors affecting accuracy of pretender cost estimate are: Level of competitors in the tendering; Material price changes Communications with suppliers; Communications with client; and Estimating method used, with important indexes values of 79.9, 78.63, 76.76, 73.31,and 73.23 respectively. On the other hand, results indicate that timing of advertisement (weather effects), site conditions (topography, access,..etc), equipment costs, material shortage, and type of project (residential, commercial, industrial,….etc) were the lowest factors affecting accuracy of pretender cost estimate, with important index values of 52.08, 52.05, 51.87, 49.28, and 46.44 respectively.


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Table 8: Overall ranks of all factors affecting accuracy of pretender cost estimate Factor Level of competitors in the tendering Material price changes Communications with suppliers Communications with client Estimating method used Labor productivity Clear contract conditions Estimator's experience Tender selection method (open, selected, negotiation, ..etc.) Client's evaluation and awarding policy Time allowed for preparing the cost estimate Method of procurement (traditional, design bid build, design and build, project management, etc) Communication and coordination with consultants Project size Material storage Clear scope definition for the client Financial conditions of the client Type of contract Availability of data base of bids on similar project (Historical cost data) Designer's experience level Equipment productivity The taxes and other financial requirements on tender Client experience in construction projects Procedure for updating cost information Project duration Accuracy and reliability of cost information The experience and skill level of the consultant Equipment availability Labor costs Advanced payment Labor availability Completeness of cost information Clear and detail drawings and specifications Number of competitors in the market Location of project Communications and coordination between designers Equipment conditions Volume of consultant's workload during estimation Construction techniques requirements Timing of advertisement ( weather effects) Site conditions (topography, access,..etc) Equipment costs Material shortage Type of project (residential, commercial, industrial,….etc)

Owners' view IMP.I (%) Rank 79.90 1 78.63 2 76.76 3 73.31 4 73.23 5 72.81 6 72.33 7 72.10 8 70.13 9 68.55 10 68.19 11 68.13 12 66.98 66.63 66.34 65.62 64.79 64.48 64.19 63.37 63.23 63.20 63.13 62.66 62.60 62.50 61.89 61.22 60.76 59.57 58.48 58.08 58.04 57.65 57.55 57.19 56.16 55.76 53.51 52.08 52.05 51.87 49.28 46.44

13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44


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4.2 Groups ranking The identified 44 factors affecting accuracy of pretender cost estimate are grouped into six groups. Ranking of these groups associated with degree of importance by owners is presented in Table 9. Results show that the top affecting group is cost estimating (IMP.I = 65.85), closely followed by clients group (IMP.I = 65.81) and contract and tendering group (IMP.I = 65.27). The table also shows that the groups’ importance index has short span; it is ranging from 56 to 66. The results show that the project characteristics group is the one with the lowest importance index of value = 56.46. Table 9: Main groups ranking Group

Owners' view IMP.I (%) Rank Factors related to cost estimating 65.85 1 Factors related to clients 65.81 2 Factors related to contract and tendering 65.27 3 Factors related to consultants and design 63.76 4 Factors related to labors, material and equipments 61.88 5 Factors related to project characteristics 56.46 6

4.3 Statistical analyses Table 10 presents the responses’ statistical analyses as assessed by the surveyed owners. The table contains the computation of the weighted mean, standard deviation (Sn), and coefficient of variation (C.V). These statistics are used to interpret the dispersion, compactness, and the degree of homogeneity of the collected data. Results show that the standard deviation of the responses is ranging from 0.49 to 0.91. A visual indication obtained from the scatter diagram shown in Figure 1 indicates that the data has good compactness, meaning that there is a good data consistency and agreement between participants on the importance of the identified factors. Table 10 also shows that the responses have a reasonable coefficient of variation, ranging from 12.31% to 39.25%. Visually, it can be seen from Figure 2 that as the factor weighted mean increases, the coefficient of variation decreases, meaning that the participants are highly agreed on the importance of the top affecting factors.


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Table 10: Statistical analyses of the responses Factor X' Sn C.V (%) Level of competitors in the tendering 4.00 0.51 12.73 Material price changes 3.93 0.59 14.89 Communications with suppliers 3.84 0.49 12.81 Communications with client 3.67 0.52 14.29 Estimating method used 3.66 0.52 14.09 Labor productivity 3.64 0.66 18.19 Clear contract conditions 3.62 0.64 17.67 Estimator's experience 3.60 0.73 20.29 Tender selection method (open, selected, negotiation, ..etc.) 3.51 0.87 24.82 Client's evaluation and awarding policy 3.43 0.84 24.49 Time allowed for preparing the cost estimate 3.41 0.55 16.03 Method of procurement (traditional, design bid build, design and 3.41 0.85 25.09 build, project management, etc) Communication and coordination with consultants 3.35 0.75 22.30 Project size 3.33 0.70 21.03 Material storage 3.32 0.83 25.07 Clear scope definition for the client 3.28 0.67 20.42 Financial conditions of the client 3.24 0.75 23.29 Type of contract 3.22 0.59 18.39 Availability of data base of bids on similar project (Historical cost data) 3.21 0.64 19.91 Designer's experience level 3.17 0.77 24.30 Equipment productivity 3.16 0.82 26.06 The taxes and other financial requirements on tender 3.16 0.75 23.88 Client experience in construction projects 3.16 0.64 20.25 Procedure for updating cost information 3.13 0.80 25.56 Project duration 3.13 0.62 19.68 Accuracy and reliability of cost information 3.13 0.85 27.10 The experience and skill level of the consultant 3.09 0.73 23.64 Equipment availability 3.06 0.68 22.14 Labor costs 3.04 0.88 28.89 Advanced payment 2.98 0.76 25.60 Labor availability 2.92 0.70 23.97 Completeness of cost information 2.90 0.67 23.07 Clear and detail drawings and specifications 2.90 0.82 28.13 Number of competitors in the market 2.88 0.73 25.38 Location of project 2.88 0.75 25.96 Communications and coordination between designers 2.86 0.85 29.89 Equipment conditions 2.81 0.75 26.87 Volume of consultant's workload during estimation 2.79 0.75 27.07 Construction techniques requirements 2.68 0.75 28.21 Timing of advertisement ( weather effects) 2.60 0.75 28.68 Site conditions (topography, access,..etc) 2.60 0.73 28.11 Equipment costs 2.59 0.88 33.76 Material shortage 2.46 0.82 33.12 Type of project (residential, commercial, industrial,….etc) 2.32 0.91 39.25


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Figure 1: Mean versus standard deviation of owners' responses

Figure 2: Mean versus variation coefficient of owners' responses

5. Conclusion This study aims at identifying factors affecting accuracy of pretender cost estimate in building construction projects in Saudi Arabia from owners’ perspective. This objective is achieved through a questionnaire survey of 32 owners. The survey included 44 possible factors affecting pretender cost estimate accuracy. The survey is designed to measure the importance of the factors affecting pretender cost estimate in building construction projects. Results show that the top five important factors are: level of competitors in the tendering, material price changes, communications with suppliers, communications with client, and estimating method used. On the other hand, results indicate that timing of advertisement (weather effects), site conditions (topography, access,..etc), equipment costs, material shortage, and type of project (residential, commercial, industrial,….etc) were the lowest factors affecting accuracy


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of pretender cost estimate. Results show that pretender cost estimate accuracy is mostly affected by cost estimating factors, closely followed by clients and contract and tendering, respectively. The responses’ statistical analyses show that the data has good compactness and consistency, indicating a high agreement between participants on the importance of the identified factors. It also shows the followings: (1) the minimum factor index is 46.44, (2) the minimum group index is 56.46. These all indicate that the identified factors are highly relevant to the problem of pretender cost estimate accuracy in building construction projects in Saudi Arabia Based on the study findings, the following general recommendations are suggested to improve the cost estimating skills: (1) Check for resources and capabilities of the bidder before bid awarding, (2) there is a need to review cost estimation practice in terms of education and training required for those responsible for estimating function to do their job properly, (3) material prices, labor rates and equipments rates, should be updated continuously, (4) more communication and coordination between project participants (owner, supplier, consultant, and designer) should be done during the early stages of the project , (5) The nature of projects and their associated risks should be taken into consideration at the time of cost estimating.

ACKNOWLEDGEMENT The present research work has been undertaken within the Binladen Research Chair on Quality and Productivity Improvement in the Construction Industry funded by the Saudi Binladen Constructions Group.

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[6] Koushki, P.; Al-Rashid, K.; and Kartam, N. (2005). “Delays and cost increases in the construction of private residential projects in Kuwait.” Construction Management and Economics, Vol. 23, No. 3, pp. 285-294. [7] Mahamid, I. (2013). Contractors’ perception of risk factors affecting cost overrun in building projects in Palestine. The IES Journal Part A: Civil & Structural Engineering, DOI:10.1080/19373260.2013.854180. [8] Mahamid, I. and Bruland, A. (2012). Cost deviation in road construction projects: The case of Palestine. Australasian Journal of Construction Economics and Building, Vol 12, No 1, pp: 58 – 71. [9] Oberlender, G. and Trost, S. (2001). Predicting accuracy of early cost estimates based on estimate quality. Journal of Construction Engineering and Management, Vol.127, No. 3, pp. 173-182. [10] Odeck, J. (2004). Cost overruns in road construction—what are their sizes and determinants? Transport Policy, 11, pp 43–53. [11] Odusami, K. and Onukwube, H. (2008). Factors affecting accuracy of pretender cost estimate in Nigeria. The construction and building research conference of the Royal Institution of Chartered Surveyors, COBRA. [12] Shash, A. and Ibrahim, A. (2005). Survey of procedures adopted by A/E firms in accounting for design variables in early cost estimates. Journal of King Saud University, Vol. 18, Eng. Sci. (1), pp. 1-17.