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An exploration into cost-influencing factors on construction projects
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ScienceDirect International Journal of Project Management 32 (2014) 850 – 860 www.elsevier.com/locate/ijproman
An exploration into cost-influencing factors on construction projects Ying-Mei Cheng ⁎ Department of Civil Engineering and Hazard Mitigation Design, China University of Technology, 56 Hsing-Lung Road, Section 3, Taipei 116, Taiwan, ROC Received 22 May 2013; received in revised form 30 August 2013; accepted 3 October 2013 Available online 25 October 2013
Abstract Construction cost overrun is a common problem in construction industries. The objective of this research is to extract the key cost-influencing factors with new concept and methods to help control the expenditure. Hence, this research adopts the Modified Delphi Method (MDM) with 2 groups and 2 rounds and Kawakita Jiro method (KJ) to consolidate the experts' opinions and identify and rank the key factors that affect project costs. Ninety cost-influencing factors are collected from literary review and interviews with experts with practical cost control experiences in the construction companies (Group 1). The KJ method is used to consolidate these factors into 4 categories and down to a total of 42 factors. 2 rounds of questionnaires are then conducted to filter the key factors. In order to verify views of those in the first group, Group 2 consists of experienced experts from the public sectors, consulting firms and construction companies as a comparison. Results of the analysis indicate that there are 16 key cost-influencing factors. Severity Index computation was then adopted to rank these key cost-influencing factors. The study renders that clearly defined scope of project in the contract and cost control are the major determinants for cost overrun. © 2013 Elsevier Ltd. APM and IPMA. All rights reserved. Keywords: Cost-influencing factors; Cost control; Modified Delphi Method; KJ method
1. Introduction It's customary in construction industries to win projects with the lowest bids. Therefore, without controlling key costinfluencing factors, construction companies will not be able to control the expenditure effectively, which will in turn increase project costs and affect overall profit. In fact, construction cost overrun is a common problem in construction industries. Flyvbjerg et al. (2002) pointed out that historically, large construction projects have been plagued by cost and schedule overruns. Shane et al. (2009) stated that final project costs have been higher than the cost estimates prepared in too many cases. Doloi (2011) brought up that cost overrun is a chronic problem for most projects. Love et al. (2013) calculated cost
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overruns from 276 construction and engineering projects and revealed a mean cost overrun of 12.22%. No significant differences for cost overruns were found among contract size, project type, and procurement method. Kaming et al. (1997) also discussed construction time and cost overruns in developing countries such as Nigeria, Saudi Arabia and Indonesia. However, construction overrun is not unique to developing countries. It is a worldwide issue worsened by the global financial crisis due to increasing price competition. As construction companies usually rely on various financing approaches to meet their capital needs during construction, the inherent financial constraint poses further influence on the overall costs and the ultimate profit if the key cost-influencing factors cannot be controlled. Therefore, this paper takes the standpoint of the construction companies to explore and discuss key factors that affect project costs during construction. The methodology integrates literary review, interviews, the KJ method (Kawakita Jiro method, affinity diagram), and the Delphi Expert Assessment (with 2 groups and
Y.-M. Cheng / International Journal of Project Management 32 (2014) 850–860
2 rounds) to locate the key cost-influencing factors from various layers, and to assist the construction companies with effective cost control both during the preparation stage and after the construction proceeds in order to reduce risks derived from costs or escalating expenditure. 2. Literature review Kaming et al. (1997) identified factors influencing construction time and cost overruns in Indonesia and analyzed the correlation between the two. The scope of this particular research only focuses on the high-rise projects. Dissanayaka and Kumaraswamy (1999) identified and grouped factors significantly related to time and cost performance and then developed the time and cost overrun models. Chang (2002) identified the reasons for cost and schedule increases and classified them into 3 aspects — owner's control, consultant control, and beyond control. Although Chang used case studies to analyze the reasons and qualify their contributions, he only focused on engineering design projects. Elhag et al. (2005) mainly takes the standpoint of the quantity surveyors to explore cost-influencing factors. He identified 67 variables which affect pre-tender construction cost estimates through literature and interviews. These factors are divided into 6 categories — client characteristics, consultant and design parameters, contractor attributes, project characteristics, contract procedures and procurement methods, and external factors and market conditions. Questionnaires were then used to evaluate and rank these factors. Chen and Hsu (2008) identified and quantified the factors that influence corporate financing. He concluded 4 component groups with corresponding weight and 14 significant factors. Shane et al. (2009) proposed escalation factors for construction project costs through case studies. He identified 11 internal factors and 7 external factors and verified them with over 20 U.S. state highway agencies through interviews. Chan (2012) investigated the principal factors affecting project overheads with questionnaire. Eight factors were extracted from 27 variables. Doloi (2013) identified 48 major factors affecting cost overruns and analyzed the relationship among the factors and 3 key stakeholders — client, consultant, and contractor. The previously referenced studies successfully utilized literature, interviews, questionnaire or MDM to determine the critical factors which impact the project cost. Therefore, based on the success of the above-mentioned studies and with new concepts introduced to existing methods, this study will identify the key cost-influencing factors with a more deliberate process. This research is conducted in 2 stages. During the first stage, cost-influencing factors are deduced from the construction company's perspective. The perspectives of the public sector and consulting firms (client) are then introduced to further identify the key factors. The research process is explained in the following section. 3. Research process The Delphi method is suitable for extracting usable data from personal experiences which can be transformed into empirical data for future studies. As shown in the flowchart in
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Fig. 1, this study adopts the Modified Delphi Method (MDM) with 2 groups and 2 rounds to identify the key cost-influencing factors. The reasons for adopting 2 groups are to verify the construction company's view from a different perspective and to give the study more objectivity. Literary review is first conducted on local and international literatures concerning project cost control. Experts with years of cost control experiences in the industry are then interviewed to provide an understanding of the actual cost control process and issues as well as a preliminary list of cost-influencing factors recognized by the industry or in the literatures. Meanwhile, the KJ method is adopted to organize the factors collected at this point and develop a more refined list. The factors are then categorized and used in the questionnaires for the MDM, and the questionnaires are distributed to 2 groups of experts in 2 separate rounds. The cost-influencing factors obtained from expert assessments are then ranked by Severity Index (SI).
4. Research methodology 4.1. KJ method The KJ method is a qualitative technique developed by Kawakita Jiro in 1953. It adopts the bottom-up sorting process and is very useful for classifying data. It is used to organize data into useful categories, or in other words, transform data into
Determine the Research Direction
Collection and Organization of cost-influencing factors Interview with experts (Group 1)
Literary Review
Organize the factors using the KJ method Design the first round of questionnaire
MDM 2 -group and 2 -round Questionnaire Group 1
Group 2
First round
First round
Questionnaire Analysis
Questionnaire Analysis
Design the second round of questionnaire
Design the second round of questionnaire
Second round
Second round
Questionnaire Analysis Filter the key factors Rank the key factors Conclusion and Recommendations
Fig. 1. Research process.
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information (Lance, 2006). Zaphiris et al. (2005) employed the KJ method to study a set of age-centered and research-based web design guidelines. Cheng and Leu (2011) integrated data mining with the KJ method to analyze bridge construction defects. To create an affinity diagram, a group of people, index cards or sticky notes, and a physical space are required. The steps in the KJ method are as follows: (1) determine the theme; (2) gather the data; (3) sort the data into groups; (4) create header cards, and (5) draw the finished diagram. In step (3), people first transfer the data onto the index cards or sticky notes, scatter the cards on a table or post the notes on a wall, and then arrange the cards according to related ideas, issues, or topics of data (Plain, 2007). The factors collected during the initial stage come from different experts and literatures and may be interrelated or with similar wording. The KJ method may effectively filter and consolidate the factors into independent factors for the use of follow-up questionnaires. 4.2. Modified Delphi Method The Delphi concept was developed by the American defense industry (Chan et al., 2001). Its characteristics include anonymity, iteration with controlled feedback and statistical response (Yeung et al., 2009). It collects the opinions of the experts in the related field through questionnaire to deal with complex issues. To keep the experts from influencing each other's opinions, the traditional Delphi utilizes one to several rounds of questionnaires anonymously. The most significant drawback is that the reiterations are time-consuming. Murry and Hammons (1955) modified the Delphi method based on special considerations. They omit the complex process of open questionnaire and replace the first round of questionnaire with literary exploration or interviews with the experts. Besides, there are innumerable applications for the Delphi method in recent years. Chan et al. (2001) used the criteria and utility factors derived from the Delphi survey technique to develop a multi-attribute procurement selection model. Yeung et al. (2009) applied the Delphi survey technique with four rounds of questionnaires with 22 experts from the construction industry to formulate a model to assess the success of relationship-based construction projects in Australia, and eight key performance indicators were selected. Hallowell and Gambatese (2010) explored the application of the Delphi method in Construction Engineering and Management (CEM), which consists of some of the researches that are applied toward CEM with recommendations on the procedures of the traditional Delphi and parameters for each stage. Ma et al. (2011) adopted the Fuzzy Delphi method and Grey Delphi method to construct three sets of road safety performance indicators. The above-mentioned Delphi applications all received decent results. In addition, the process of arriving at the cost-influencing factors from the open questionnaire is complex and difficult during the initial stage of traditional Delphi. Existing studies on similar subject matters provide ample references for this study. Many of those on the subject of cost-influencing factors adopt literary review and interview with experts to identify the factors in the initial stage (Dissanayaka and Kumaraswamy,
1999; Elhag et al., 2005; Elinwa and Buba, 1993). Considering the limited resources and weighing in the value of existing studies to this research, it seems more feasible to modify the first round of traditional Delphi (MDM) instead of that with an open-ended questionnaire and starting from scratch. Therefore, MDM (Murry and Hammons, 1955) is adopted for this study. In addition, this study is built on the foundation of existing studies to be on the cautious side and thus adopts the approach of identifying the cost-influencing factors from the literatures supplemented with interviews with experts.
5. Collection and organization of cost-influencing factors At this stage, according to the first stage of MDM, literary review (Dissanayaka and kumaraswamy, 1999; Elhag et al., 2005; Elinwa and Buba, 1993; Kaming et al., 1997; Shane et al., 2009) and individual interviews are conducted with engineers from various construction companies to identify the initial cost-influencing factors. Besides, the KJ method is also applied to help organize these factors and develop them for the questionnaire for the later stages. Chan et al. (2001) once stressed that the success of Delphi lies in the careful selection of the panel members. In order to identify eligible participants for the current Delphi study and to appropriately reflect the current conditions of the construction company, the following three criteria were devised: (1) practitioners having extensive working experience in cost control; (2) experts having a sound knowledge and understanding of cost control concepts in the construction companies; and (3) experts having current, recent or direct involvement in the management of cost control in the construction companies. Therefore, all panel members selected for this study were once or are currently employed in the Grade A comprehensive construction enterprises (with a capital over NT$225 millions) in Taipei, Taiwan. They include cost control managers and senior engineers who are involved in the cost control process, among which 1 has over 20 years of experience, 3 with 10 to 20 years of experience, and 8 with 5 to 10 years. According to Hallowell and Gambatese (2010), most studies incorporate 8 and 16 panelists while a minimum of 8 is recommended and 12 are selected, which is within the reasonable range. 90 initial cost-influencing factors are compiled at this stage. They are further consolidated into 42 factors under 4 categories with KJ method. The KJ processes are discussed by the researcher and some of the experts of Group 1. For example, in Fig. 3, user demand, structure type, project type and project location are factors that are relevant to each other. Therefore, scale of construction is used instead of these 4 factors. Project scope specified in the bid belongs to clearly define the scope of project in the contract, so they are combined as one factor. All of the factors: scale of construction, clearly define the scope of project in the contract, contract types, and so on are all related to contract scope, so the factor, Scope of Contract is used instead. According to the organization by the KJ processes, the results are shown in Figs. 2–5, the category of “Environmental and Circumstantial Influence” includes 8 factors, “Scope of Contract” includes 8,
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Environmental and circumstantial influence
Interest rate on bank loans
The fluctuations in labor cost is too great Natural disaster
Changes in mortgage rates
Climate factor
Political environment The fluctuations in commodity price is too great
Geology, topography
The real estate prospect
Gross domestic products (GDP)
Fig. 2. Affinity diagram for environmental and circumstantial influence.
“Project Risks” contains 10, and “Management and Technique” contains 16 factors.
Group 2 is no longer being employed in the construction companies. The purpose is to compare and verify the views and perspectives between members working in the construction company (Group 1) and those who do not (Group 2). 5 panel members in Group 2 have over 20 years of experience, 3 with 10 to 20 years of experience, and 3 with 5 to 10 years of experience, a total of 11 members. The questionnaire assigns a five-point Likert scale to each of the 42 factors under the 4 categories. Separate surveys were conducted for Group 1 and Group 2 where 12 questionnaires were sent to Group 1 and 11 to Group 2. The results of the first round of questionnaire are shown in Tables 1.1 to 1.4. The means from Group 1 and Group 2 for the first round are used as the feedback for the second round of questionnaires and shown to the panel members so that they can quickly reach consensus according to the significance of the factors. The analysis of the feedback is shown in Tables 2.1 to 2.4, in which the mean values for Group 1 and Group 2 for each of the 4 categories are quite close.
6. Analysis and ranking of cost-influence factors 6.1. Modified Delphi Method with 2 groups and 2 rounds There are 2 groups of recipients for the questionnaire and 2 rounds of questionnaires were conducted to obtain the key factors. The panel members for one of the groups are those from whom the 90 initial factors were obtained (Group 1). To cross-reference the influence of these factors during construction, another group of experts (Group 2) with no involvement in selecting the factors in the initial stage were chosen for the two rounds of MDM. Group 2 consists of engineering staff or officials who are involved in cost control. 3 of them are employed in the public sector, 6 are employed in the consulting firms, and 2 in the construction companies. The emphasis for
Scope of of contract contract The level of demand on quality
Contract types
Modifications of project schedule ( ahead of schedule or stop in mid -construction )
Project quality Contract dispute (unclear drawings or guidelines/regulations) Modifications to the scope of construction
Clearly define the scope of project in the contract
The client applies/requests for modifications
Project scope specified in the bid
Scale of construction
The types of clients
User demand
Structure type
The client's way of dealing with key decisions
Project type
Project location
The client asks that the project be done ahead of schedule
Fig. 3. Affinity diagram for scope of contract.
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Project risks Project risks Protest
Stagnant project
Neighbor protests
Policy change
Tilted neighboring structure
Delayed procurement
Unexpected technical difficulties
Labor protests
Disputes in opinions over the construction drawings The project scale is too big and the project itself too complex
Inadequate construction techniques Material shortage or supply delay
The client's financial capability
Design modifications
The subcontractors bankrupted
Occupational hazards
Inadequate project listing Add new construction activities Add on to the number of activities
The gap between the construction plan and the reality is too great
Fig. 4. Affinity diagram for project risks.
Management and Technique Time management
Project control meeting
Material management
Monitor and feedback
The timetable for the materials to be delivered on site
Arrangement of construction progress
The understanding of operational procedures during project management
Project valuation does not match the collected payment
The client and engineer understand the difficulties in the actual operation and made appropriate decisions
Procurement contract
The order of construction projects
Subcontractor's valuation
Regular budget update
Cost control
Personnel training Project manager's capability Budget exceptions
Labor attendance
Project manager's leadership project manager's understanding of the operational procedure
Whether the high-level management decentralizes the power Project team (coordination capability and the understanding of operational procedure) Interactions among the project participants
Coordination among the team members
Project manager's practical experience Job site safety and health management Project manager's coordination capability Carry out supervision Project manager's risk management ability
Whether the monitoring is implemented Coordination and mutual understanding among the high-level management
Team work among the subcontractors
Coordination between the project manager and the high-level management Conflicts that occur while the high-level management manages the project
Practical experience the lack of experience for this type of project
Construction methods
Subcontractors' construction techniques
Construction machinery and equipment
Subcontractors' financial difficulties
Replacement of construction equipment
Support from the high-level management Terminate the contractor's contract and re-issue the contract Coordination between the project manager and subcontractors Attitudes of the project manager and the subcontractors Subcontractors' passive attitude toward project management
Knowledge and experience Bid rigging
Quality of the labor and engineering staff Competitive bidding Construction personnel's real-time decision-making
Fig. 5. Affinity diagram for management and technique.
Bid preparation period
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Table 1.1 First round results — environmental and circumstantial influence.
6.2. Analysis
Factor
To further identify the significant cost-influencing factors among the 42 known factors, the ones that fall out of the measures of central tendency or with a measure of variation that's too great are excluded. The qualifications include: (1) the mean of the single factor is greater than 3 and larger than the mean of the factors within that category; (2) the quartile range is equal to or less than 0.5; and (3) the standard deviation of the single factor is equal to or less than 1. Table 3 shows factors from both Groups 1 and 2 that meet all three of the above mentioned qualifications. There are 4 factors each under the categories of Environmental and Circumstantial Influence and Scope of Contract, 2 under Project Risks, and 6 under Management and Technique. The radar charts in Figs. 6 to 8 show the comparison of the mean, standard deviation and quartile ranges between the 2 groups. In terms of the mean (as shown in Fig. 6), the two groups hold opposite views toward factor A-4, High Fluctuations in Commodity Price. The mean from Group 1 is 4.92 with a standard deviation of 0.3 and a quartile range of 0. Among the 12 panel members, 11 gave the maximum value of 5, and only 1 gave 4. A reasonable explanation would be that the construction companies often have to absorb the changes in cost as a result of fluctuating commodity price. Therefore, 11 members held the same view
Group 1
Group 2
Mean Standard Quartile Mean Standard Quartile deviation ranges deviation ranges Climate factor Natural disaster Geology, Topography Political environment High fluctuation in labor cost High fluctuation in commodity Gross domestic products (GDP) Interest rate on bank loans Average
4.00 4.00 4.42
1.10 0.70 0.80
0.60 0.30 0.50
4.09 4.09 4.18
0.70 0.8 0.6
0.30 0.8 0.3
2.92 3.83
0.80 0.90
0.10 0.60
3.64 3.55
1.2 0.8
1.3 0.5
4.58
0.50
0.50
4.55
0.5
0.5
3.58
0.90
0.50
3.27
1.1
0.8
3.67
0.90
0.60
3.82
0.9
0.8
3.88
0.83
0.46
3.90
0.83
0.66
Therefore, it can be concluded that the perspective of the construction company match that of the client. The Scope of Contract and Project Risks are the two categories with higher influences on project costs. In contrast, the influence of the Environmental and Circumstantial factors is relatively low.
Table 1.2 First round results — scope of contract. Factor
Clearly define the scope of project in the contract Scale of construction The types of clients Contract types Modifications to the scope of construction Modifications of project schedule (ahead of schedule or stop in mid-construction) Contract dispute (unclear drawings or guidelines/regulations) The level of demand on quality Average
Group 1
Group 2
Mean
Standard deviation
Quartile ranges
Mean
Standard deviation
Quartile ranges
4.75 3.33 3.75 3.83 4.33 4.58
0.40 0.90 0.70 0.80 0.60 0.50
0.10 0.50 0.10 0.10 0.50 0.50
4.55 3.73 3.82 3.82 4.09 4.09
0.7 0.7 0.7 0.7 0.9 0.5
0.5 0.3 0.5 0 1 0
4.58 4.42 4.20
0.50 0.60 0.63
0.50 0.50 0.35
4.45 4.09 4.08
0.5 0.9 0.70
0.5 0.5 0.41
Table 1.3 First round results — project risks. Factor
Group 1
Group 2
Mean
Standard deviation
Quartile ranges
Mean
Standard deviation
Quartile ranges
Design modifications Protest The client's financial capability Stagnant project Occupational hazards Inadequate project listing The vendors/contractors/subcontractors went bankrupted Inadequate construction techniques The gap between the construction plan and the reality is too great. Material shortage or supply delay Average
4.33 3.75 4.42 4.42 4.67 4.17 3.75 4.08 4.42 4.58 4.26
0.70 0.70 0.60 0.50 0.50 0.70 0.60 0.80 0.80 0.60 0.65
0.50 0.50 0.50 0.50 0.50 0.50 0.50 0.60 0.50 0.50 0.51
3.91 4.55 3.91 4.00 4.45 4.00 4.36 4.55 4.45 4.73 4.29
0.9 0.7 0.8 0.6 0.5 0.9 0.9 0.5 0.7 0.6 0.71
0.5 0.5 0 0 0.5 0.3 0.5 0.5 0.5 0 0.33
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Table 1.4 First round results — management and technique. Factor
Group 1
Cost control Project control meeting Labor attendance Carry out supervision/monitoring Project valuation does not match the collected payment. Whether the high-level management decentralizes the power. Staff/personnel training Regular budget update Job site safety and sanitation/health management Budget exceptions Material management Practical experience Procurement contract Time management The project manager's capability Project team (coordination capability and the understanding of operational procedure) Average
Group 2
Mean
Standard deviation
Quartile ranges
Mean
Standard deviation
Quartile ranges
4.75 4.00 3.67 4.17 4.08 4.50 4.08 3.75 4.33 3.83 4.17 4.33 4.50 4.50 4.67 4.58
0.40 0.70 0.70 0.70 0.60 0.50 0.60 1.00 0.90 0.70 0.60 0.50 0.50 0.50 0.50 0.50
0.10 0.30 0.50 0.50 0.10 0.50 0.10 0.60 1.00 0.50 0.10 0.50 0.50 0.50 0.50 0.50
4.64 4.18 3.91 4.18 4.36 4.09 3.91 4.09 3.91 3.91 4.18 4.64 4.18 4.18 4.36 4.45
0.5 0.6 0.7 0.6 0.9 0.7 0.8 0.8 0.5 0.5 0.8 0.5 1.1 0.7 0.9 0.7
0.5 0.3 0 0.3 0.5 0.3 0 0.3 0 0 0.5 0.5 0.5 0.5 0.5 0.5
4.24
0.62
0.43
4.21
0.72
0.34
and gave the rating of 5. The mean for Group 2 is 4.00 with a standard deviation of 0.7 and a quartile range of 0.5. 3 of the 11 panel members gave the maximum value of 5, and 3 gave the value of 3. Members in Group 2 are from different sectors. Although they each hold a different view, with a mean of 4.00,
the group still thinks that factor A-4 holds certain influence over construction costs. Figs. 7 and 8 show the comparison of the standard deviation and quartile range between the two groups. It is shown that the standard deviation for factor C-2 from Group 1, Material Shortage or Supply Delay, is 0.9, the
Table 2.1 Second round results — environmental and circumstantial influence. Factor
Climate factor Natural disaster Geology, topography Political environment High fluctuation in labor cost High fluctuation in commodity price Gross domestic products (GDP) Interest rate on bank loans Average
Group 1
Group 2
Mean
Standard deviation
Quartile ranges
Mean
Standard deviation
Quartile ranges
4.00 3.75 4.33 3.00 3.33 4.92 3.00 3.67 3.75
0.60 0.4 0.6 0.7 0.7 0.3 0.6 0.7 0.58
0.00 0.1 0.5 0.3 0.5 0 0 0.5 0.24
4.27 4.27 4.09 3.55 3.36 4.00 3.18 3.55 3.78
0.40 0.4 0.7 0.8 0.6 0.7 0.7 0.7 0.63
0.30 0.3 0.3 0.5 0.5 0.5 0.5 0.5 0.43
Table 2.2 Second round results — scope of contract. Factor
Clearly define the scope of project in the contract Scale of construction The types of clients Contract types Modifications to the scope of construction Modifications of project schedule (ahead of schedule or stop in mid-construction) Contract dispute (unclear drawings or guidelines/regulations) The level of demand on quality Average
Group 1
Group 2
Mean
Standard deviation
Quartile ranges
Mean
Standard deviation
Quartile ranges
4.83 3.33 3.83 3.58 4.25 4.08
0.4 0.6 0.8 0.9 0.6 0.6
0 0.5 0.1 0.5 0.5 0.1
4.64 3.64 3.64 3.55 4.45 4.36
0.5 0.8 0.6 0.7 0.7 0.6
0.5 0.5 0.5 0.5 0.5 0.5
4.83 4.42 4.15
0.4 0.6 0.61
0 0.5 0.28
4.45 4.27 4.13
0.7 0.9 0.69
0.5 0.5 0.50
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Table 2.3 Second round results — project risks. Factor
Group 1
Design modifications Protest The client's financial capability Stagnant project Occupational hazards Inadequate project listing The vendors/contractors/subcontractors went bankrupted Inadequate construction techniques The gap between the construction plan and the reality is too great. Material shortage or supply delay Average
Group 2
Mean
Standard deviation
Quartile ranges
Mean
Standard deviation
Quartile ranges
4.33 3.33 4.67 4.17 4.75 4.08 3.33 3.92 4.33 4.33 4.13
0.6 0.6 0.5 0.9 0.4 0.8 0.9 0.5 0.7 0.9 0.68
0.5 0.1 0.5 0.5 0.1 0.6 0.5 0 0.5 0.5 0.38
3.91 4.45 3.82 4.18 4.00 3.82 4.00 4.55 4.64 4.64 4.20
0.9 0.5 0.6 0.6 0.7 0.7 0.9 0.8 0.6 0.6 0.69
0.5 0.5 0.3 0.3 0.5 0 0.3 0.3 0.3 0.3 0.33
quartile range is 0.5 and the mean is 4.33. Also, 7 of the 12 members gave the rating of 5, and only 1 member gave the rating of 2. Therefore, it is determined that this factor should be considered a main cost-influencing factor. In addition, the figures also show that the standard deviation of factor B-4 from Group 2, The Level of Demand on Quality, is 0.9, and the mean is 4.27. 5 of the 11 members rated it 5 and only 1 member rated it 2. Therefore it is also considered a main cost-influencing factor. After summarizing the analysis from the MDM with 2 groups and 2 rounds, 16 key cost-influencing factors were identified.
Shash (1993) recommended this method for the analysis of ordinal data collected through the Likert scale. Elhag et al. (2005), Chan (2012), Rahman et al. (2013), and Olawale and Sun (2013) also used the same approach. The SI is as follow: ! 5 X 100% SI ¼ ð1Þ wi f i n i¼1 where i represents the ratings 1–5, fi is the frequency of responses, n is the total number of responses, and wi is the weight for each rating: i A
ð2Þ
6.3. Ranking result
wi ¼
To rank the 16 key factors, the second round of the questionnaires was sent to the 23 panel members in both groups. Then Severity Index (SI), also known as Relative Importance Index (RII) was adopted to rank the cost factors.
where A is the highest score (i.e. 5 in this case). The rankings of the means of SI for the 4 categories are shown in Table 3. It is evident that the Scope of Contract and Project Risks are the two categories that pose higher influences over project costs. In
Table 2.4 Second round results — management and technique. Factor
Cost control Project control meeting Labor attendance Carry out supervision/monitoring Project valuation does not match the collected payment. Whether the high-level management decentralizes the power. Staff/personnel training Regular budget update Job site safety and sanitation/health management Budget exceptions Material management Practical experience Procurement contract Time management The project manager's capability Project team (coordination capability and the understanding of operational procedure) Average
Group 1
Group 2
Mean
Standard deviation
Quartile ranges
Mean
Standard deviation
Quartile ranges
4.83 3.92 3.25 3.83 4.08 4.08 3.50 3.50 4.00 3.58 4.17 4.50 4.42 4.50 4.42 4.42
0.4 0.3 0.4 0.6 0.6 0.8 0.6 1 0.7 1 0.6 0.6 0.6 0.6 0.6 0.6
0 0 0.1 0.1 0.1 0.6 0.5 0.5 0.3 0.6 0.1 0.5 0.5 0.5 0.5 0.5
4.64 4.00 3.55 3.82 4.55 4.09 3.73 4.00 3.82 3.55 3.91 4.27 4.09 4.36 4.00 4.27
0.5 0.7 0.7 0.7 0.5 0.8 0.7 0.6 0.9 0.5 0.3 0.4 0.5 0.5 1 0.6
0.5 0.5 0.5 0 0.5 0.3 0.3 0 0.8 0.5 0 0.3 0 0.5 0.8 0.5
4.08
0.62
0.35
4.05
0.62
0.38
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Table 3 Mean SI for the categories with key cost — influencing factors. Category
D-6
Factor
terms of the rankings for the individual factors (as shown in Table 4), Clearly Defined Scope of Project in the Contract and Cost Control are the most important cost impact factors with 94.78. The second highest is Contract Dispute with 93.04, which clearly makes it a significant factor. If the contract does not clearly delineate the scope of project, or if the construction drawings are unclear with ambiguous specifications, expectations from both parties may differ and cause unnecessary disputes after the construction commences. In addition, price fluctuation is another main factor for cost overruns. For projects of a larger scale or with longer construction periods, it is vital to understand the fluctuations in prices in recent years and the acceptable level of fluctuation. The construction companies should examine whether the contract contains stipulations on adjustments for price index. Price fluctuation should also be monitored regularly and reflected to the clients. Finally, although
5.00
D-4
0.40
D-3
B-1
D-2 D-1
B-3 C-2
B-4 C-1
Fig. 7. Radar chart for standard deviation comparison between the two groups.
Geology, Topography, Climate Factors, and Natural Disasters are the lowest ranking factors, they are still selected among the 46 initial factors and have a certain degree of influence over project costs. 6.4. Case study Construction projects are large scale in nature. They involve long project period, and each is distinctive and complex in its own way. In addition, the clients and contractors' abilities are also at play, which may affect the project positively or negatively. The factors may also be in any form. For example, the regional requisition for Taiwan High Speed Rail station covers a geographic area of 141.48 ha. The public construction project involves grading, road improvement, drainage, public lighting, transportation infrastructure, sewage, irrigation and plant relocation. The project also involves common duct projects and utility contracting projects. The contract stipulated that the total cost for the project was NT$1,126,867,413 and the project period was 1060 calendar days, the final project cost was NT$ 1,116,204,121, a decrease of NT$10,663,292 (LCEB,
A-2
0.50
A-2
0.40
D-5
A-3
A-3
0.30 D-4
A-4
0.20
A-4
0.10
1.00
Group 1
0.00
B-1
D-2 D-1
Group 1
0.00
D-3
B-1
Group 2
B-2 B-3 C-2
Group 2
B-2
D-6
2.00
D-3
Group 1
0.00
3.00 D-4
A-4
0.20
A-1
4.00
D-5
A-3
0.60
A-1 D-6
A-2
0.80
D-5
Environmental and circumstantial 1. Climate factor influence (A) 2. Natural disaster (SI = 84.13) 3. Geology, Topography 4. High fluctuation in commodity Scope of contract (B) 1. Clearly define the scope of project in (SI = 90.44) the contract 2. Modifications to the scope of construction 3. Contract dispute (unclear drawings or guidelines/regulations) 4. The level of demand on quality Project risks (C) 1. The gap between the construction plan (SI = 89.57) and the reality is too great 2. Material shortage or supply delay Management and technique (D) 1. Cost control (SI = 88.26) 2. Project valuation does not match the collected payment 3. Practical experience 4. Procurement contract 5. Time management 6. Project team (coordination capability and the understanding of operational procedure)
1.00
B-4 C-1
Fig. 6. Radar chart for mean comparison between the two groups.
D-2
Group 2
B-2 B-3
D-1 C-2
B-4 C-1
Fig. 8. Radar chart for quartile range comparison between the two groups.
Y.-M. Cheng / International Journal of Project Management 32 (2014) 850–860 Table 4 Ranking of the key cost — influencing factors. N0
Factor
7. Conclusion SI Rank (Severity Index)
B-1 Clearly define the scope of project in the contract D-1 Cost control B-3 Contract dispute (unclear drawings or guidelines/regulations) A-4 High fluctuation in commodity C-1 The gap between the construction plan and the reality is too great C-2 Material shortage or supply delay D-5 Time management D-3 Practical experience B-2 Modifications to the scope of construction B-4 The level of demand on quality D-6 Project team (coordination capability and the understanding of operational procedure) D-2 Project valuation does not match the collected payment D-4 Procurement contract A-3 Geology, topography A-1 Climate factor A-2 Natural disaster
859
94.78
1
94.78 93.04
1 2
89.57 89.57
3 3
89.57 88.70 87.83 86.96 86.96 86.96
3 4 5 6 6 6
86.09
7
85.22 84.35 82.61 80.00
8 9 10 11
2004). This is a successful case of cost control. Overall, the contract for this project clearly defines the scope and the project costs are well controlled. However, this project involves huge amount of capital and a vast number of factors are at play. Therefore, only public construction projects and common duct projects with greater variations in costs are used for this case study. Table 5 shows the effects of major cost-influencing factors for each aspect and the costs involved. It also indicates that the factors identified in this study agree with those from actual practice. It confirms that the final costs are closely associated with how well the factors are controlled. In additional note, though project costs were affected by the typhoon and inflation, they are within the scope of anticipated burden of risks (LCEB, 2005).
Many literatures and actual projects indicate that construction cost overrun is a common problem in the construction field. Identifying the cost-influencing factors is the first step toward addressing such problem. If construction companies can effectively control these key factors and formulate prevention strategies, it is possible not only to avoid cost overrun, but also to increase the overall profits for the project. In order to factually provide the key cost-influencing factors to the construction companies, the cost-influencing factors are analyzed and discussed from the perspectives of the construction companies. The KJ method and MDM with 2 groups and 2 rounds are utilized to improve the traditional Delphi method, and Severity Index (SI) computation was adopted to rank the factors. According to the result of the SI, the highest to the lowest categories are Scope of Contract, Project Risks, Management and Technique, and Environmental and Circumstantial Influence. There are 16 key cost-influencing factors in these 4 categories. Factors with the strongest influence include Clearly Define the Scope of Project in the Contract, Cost Control and Contract Dispute. In practice, construction companies must clearly understand the client's needs through communication during the initial stage of the project. They must have clear understanding of the scope of the contract and ask the clients for necessary clarifications regarding the drawings and specifications prior to signing the contract to avoid pricing disputes. Additionally, during project implementation, the contractors should fully implement cost-control measures. Construction companies can also use the remaining factors to conduct a thorough investigation that is tailored to the characteristics of the project and the client prior to the project commences in order to minimize uncertainties and reduce the chance of cost overruns. Abbreviations CEM Construction Engineering and Management KJ Kawakita Jiro method, affinity diagram MDM Modified Delphi Method
Table 5 Effect of cost-influencing factors on public construction and common duct projects. Category
Contract stipulated costs (NT$)
Increase/ Details (factors) decrease (NT$)
Public construction project
740,870,943
− 8,520,717
Common duct project
186,310,553
3,376,191
1. For items whose actual quantities cannot be confirmed during the planning and design stage, the contract stipulated that the payment schedule is based on actual completion. Examples include grit chambers, road pavement and compressed concrete paving units, which were significantly reduced from the original estimate. (B-1) 2. Fully implement cost control and regularly review the required quantity and construction costs. (D-1) 1. Contract omissions. (B-3) 2. Design changes due to site conditions. (B-2, C-1) 3. Unfamiliarity with local culture, which affected the design of the manhole cover. The client intervened later on for the redesign. (C-1) 4. The drilling indicated inconsistency with current conditions. Additional backfill required. (C-1) 5. Poor control over the transfer schedule and unclearly defined responsibility resulted in theft finished installations. (D-5, D-6) 6. Project redo due to poor construction quality. (B-4)
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RII SI
Y.-M. Cheng / International Journal of Project Management 32 (2014) 850–860
Relative Importance Index Severity Index
Acknowledgments The author would like to thank all participating experts, especially Kuang-Hu Cheng, former worksite director of Land Consolidation Engineering Bureau and Yu-Ming Liu, senior engineer with CECI Engineering Consultants, without their valuable contributions this research would not have been possible. Moreover, the authors would like to acknowledge the reviewers for contributing helpful suggestions and insightful comments, which greatly improved the quality of this paper. References Chan, C.T.W., 2012. The principal factors affecting construction project overhead expenses: an exploratory factor analysis approach. Constr. Manage. Econ. 30 (10), 903–914. Chan, A.P.C., Yung, E.H.K., Lam, P.T.I., Tam, C.M., Cheung, S.O., 2001. Application of Delphi method in selection of procurement systems for construction projects. Constr. Manage. Econ. 19 (7), 699–718. Chang, A.S., 2002. Reasons for cost and schedule increase for engineering design projects. J. Manage. Eng. 18 (1), 29–36. Chen, J.H., Hsu, S.C., 2008. Quantifying impact factors of corporate financing: engineering consulting firms. J. Manage. Eng. 24 (2), 96–104. Cheng, Y.M., Leu, S.S., 2011. Integrating data mining with KJ method to classify bridge construction defects. Expert Syst. Appl. 38 (6), 7143–7150. Dissanayaka, S.M., Kumaraswamy, M.M., 1999. Evaluation of factors affecting time and cost performance in Hong Kong building project. Eng. Constr. Archit. Manage. 6 (3), 287–298. Doloi, H.K., 2011. Understanding stakeholders' perspective of cost estimation in project management. Int. J. Proj. Manage. 29, 622–636. Doloi, H., 2013. Cost overruns and failure in project management: understanding the roles of key stakeholders in construction projects. J. Constr. Eng. Manage. 139 (3), 267–279. Elhag, T.M.S., Boussabaine, A.H., Ballal, T.M.A., 2005. Critical determinants of construction tendering costs: quantity surveyors standpoint. Int. J. Proj. Manage. 23, 538–545.
Elinwa, A.U., Buba, S.A., 1993. Construction cost factors in Nigeria. J. Constr. Eng. Manage. 119 (4), 698–713. Flyvbjerg, Bent, Holm, Skamris, Mette, K., Buhl, Soren L., 2002. Underestimating costs in public works projects: error or lie? J. Am. Plan. Assoc. 68 (3), 279–295. Hallowell, M.R., Gambatese, J.A., 2010. Qualitative research: application of the Delphi method to CEM research. J. Constr. Eng. Manage. 136 (1), 99–107. Kaming, P.F., Olomolaiye, P.O., Holt, G.D., Harris, F.C., 1997. Factors influencing construction time and cost overruns on high-rise projects in Indonesia. Constr. Manage. Econ. 15, 83–94. Lance, D., 2006. Creating an Affinity Diagram. LL Decker Associates, Inc.(Helping organizations change). LCEB, 2004. Land Consolidation Engineering Bureau, Ministry of the Interior, Expense Report, Regional Requisition for Taiwan High Speed Rail Taoyuan Station. LCEB, 2005. Land Consolidation Engineering Bureau, Ministry of the Interior, Evaluation Report, Regional Requisition for Taiwan High Speed Rail Taoyuan Station. Love, P.E.D., Wang, X., Sing, C.P., Tiong, R.L.K., 2013. Determining the probability of project cost overruns. J. Constr. Eng. Manage. 139 (3), 321–330. Ma, Z., Shao, C., Mac, S., Ye, Z., 2011. Constructing road safety performance indicators using Fuzzy Delphi method and Grey Delphi method. Expert Syst. Appl. 38, 1509–1514. Murry, J.W., Hammons, J.O., 1955. Delphi: a versatile methodology for conducting qualitative research. Rev. High. Educ. 18 (4), 423–436. Olawale, Y., Sun, M., 2013. PCIM: project control and inhibiting-factors management model. J. Manage. Eng. 29 (1), 60–70. Plain, C., 2007. Build an affinity for KJ method. Qual. Prog. 40 (3), 88. Rahman, I.A., Memon, A.H., Karim, A.T.A., 2013. Significant factors causing cost overruns in large construction projects in Malaysia. J. Appl. Sci. 13 (2), 286–293. Shane, J.S.A., Molenaar, K.R., Anderson, S., Schexnayder, C., 2009. Construction project cost escalation factors. J. Manage. Eng. 25 (4), 221–229. Shash, A.A., 1993. Factors considered in tendering decisions by top UK contractors. Constr. Manage. Econ. 11 (2), 111–118. Yeung, J.F.Y., Chan, A.P.C., Chan, D.W.M., 2009. Developing a performance index for relationship-based construction projects in Australia: Delphi study. J. Manage. Eng. 25 (2), 59–68. Zaphiris, P., Ghiawadwala, M., Mughal, S., 2005. Age-centered Researchbased Web Design Guidelines. Portland, Oregon, USA.
ScienceDirect International Journal of Project Management 32 (2014) 850 – 860 www.elsevier.com/locate/ijproman
An exploration into cost-influencing factors on construction projects Ying-Mei Cheng ⁎ Department of Civil Engineering and Hazard Mitigation Design, China University of Technology, 56 Hsing-Lung Road, Section 3, Taipei 116, Taiwan, ROC Received 22 May 2013; received in revised form 30 August 2013; accepted 3 October 2013 Available online 25 October 2013
Abstract Construction cost overrun is a common problem in construction industries. The objective of this research is to extract the key cost-influencing factors with new concept and methods to help control the expenditure. Hence, this research adopts the Modified Delphi Method (MDM) with 2 groups and 2 rounds and Kawakita Jiro method (KJ) to consolidate the experts' opinions and identify and rank the key factors that affect project costs. Ninety cost-influencing factors are collected from literary review and interviews with experts with practical cost control experiences in the construction companies (Group 1). The KJ method is used to consolidate these factors into 4 categories and down to a total of 42 factors. 2 rounds of questionnaires are then conducted to filter the key factors. In order to verify views of those in the first group, Group 2 consists of experienced experts from the public sectors, consulting firms and construction companies as a comparison. Results of the analysis indicate that there are 16 key cost-influencing factors. Severity Index computation was then adopted to rank these key cost-influencing factors. The study renders that clearly defined scope of project in the contract and cost control are the major determinants for cost overrun. © 2013 Elsevier Ltd. APM and IPMA. All rights reserved. Keywords: Cost-influencing factors; Cost control; Modified Delphi Method; KJ method
1. Introduction It's customary in construction industries to win projects with the lowest bids. Therefore, without controlling key costinfluencing factors, construction companies will not be able to control the expenditure effectively, which will in turn increase project costs and affect overall profit. In fact, construction cost overrun is a common problem in construction industries. Flyvbjerg et al. (2002) pointed out that historically, large construction projects have been plagued by cost and schedule overruns. Shane et al. (2009) stated that final project costs have been higher than the cost estimates prepared in too many cases. Doloi (2011) brought up that cost overrun is a chronic problem for most projects. Love et al. (2013) calculated cost
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overruns from 276 construction and engineering projects and revealed a mean cost overrun of 12.22%. No significant differences for cost overruns were found among contract size, project type, and procurement method. Kaming et al. (1997) also discussed construction time and cost overruns in developing countries such as Nigeria, Saudi Arabia and Indonesia. However, construction overrun is not unique to developing countries. It is a worldwide issue worsened by the global financial crisis due to increasing price competition. As construction companies usually rely on various financing approaches to meet their capital needs during construction, the inherent financial constraint poses further influence on the overall costs and the ultimate profit if the key cost-influencing factors cannot be controlled. Therefore, this paper takes the standpoint of the construction companies to explore and discuss key factors that affect project costs during construction. The methodology integrates literary review, interviews, the KJ method (Kawakita Jiro method, affinity diagram), and the Delphi Expert Assessment (with 2 groups and
Y.-M. Cheng / International Journal of Project Management 32 (2014) 850–860
2 rounds) to locate the key cost-influencing factors from various layers, and to assist the construction companies with effective cost control both during the preparation stage and after the construction proceeds in order to reduce risks derived from costs or escalating expenditure. 2. Literature review Kaming et al. (1997) identified factors influencing construction time and cost overruns in Indonesia and analyzed the correlation between the two. The scope of this particular research only focuses on the high-rise projects. Dissanayaka and Kumaraswamy (1999) identified and grouped factors significantly related to time and cost performance and then developed the time and cost overrun models. Chang (2002) identified the reasons for cost and schedule increases and classified them into 3 aspects — owner's control, consultant control, and beyond control. Although Chang used case studies to analyze the reasons and qualify their contributions, he only focused on engineering design projects. Elhag et al. (2005) mainly takes the standpoint of the quantity surveyors to explore cost-influencing factors. He identified 67 variables which affect pre-tender construction cost estimates through literature and interviews. These factors are divided into 6 categories — client characteristics, consultant and design parameters, contractor attributes, project characteristics, contract procedures and procurement methods, and external factors and market conditions. Questionnaires were then used to evaluate and rank these factors. Chen and Hsu (2008) identified and quantified the factors that influence corporate financing. He concluded 4 component groups with corresponding weight and 14 significant factors. Shane et al. (2009) proposed escalation factors for construction project costs through case studies. He identified 11 internal factors and 7 external factors and verified them with over 20 U.S. state highway agencies through interviews. Chan (2012) investigated the principal factors affecting project overheads with questionnaire. Eight factors were extracted from 27 variables. Doloi (2013) identified 48 major factors affecting cost overruns and analyzed the relationship among the factors and 3 key stakeholders — client, consultant, and contractor. The previously referenced studies successfully utilized literature, interviews, questionnaire or MDM to determine the critical factors which impact the project cost. Therefore, based on the success of the above-mentioned studies and with new concepts introduced to existing methods, this study will identify the key cost-influencing factors with a more deliberate process. This research is conducted in 2 stages. During the first stage, cost-influencing factors are deduced from the construction company's perspective. The perspectives of the public sector and consulting firms (client) are then introduced to further identify the key factors. The research process is explained in the following section. 3. Research process The Delphi method is suitable for extracting usable data from personal experiences which can be transformed into empirical data for future studies. As shown in the flowchart in
851
Fig. 1, this study adopts the Modified Delphi Method (MDM) with 2 groups and 2 rounds to identify the key cost-influencing factors. The reasons for adopting 2 groups are to verify the construction company's view from a different perspective and to give the study more objectivity. Literary review is first conducted on local and international literatures concerning project cost control. Experts with years of cost control experiences in the industry are then interviewed to provide an understanding of the actual cost control process and issues as well as a preliminary list of cost-influencing factors recognized by the industry or in the literatures. Meanwhile, the KJ method is adopted to organize the factors collected at this point and develop a more refined list. The factors are then categorized and used in the questionnaires for the MDM, and the questionnaires are distributed to 2 groups of experts in 2 separate rounds. The cost-influencing factors obtained from expert assessments are then ranked by Severity Index (SI).
4. Research methodology 4.1. KJ method The KJ method is a qualitative technique developed by Kawakita Jiro in 1953. It adopts the bottom-up sorting process and is very useful for classifying data. It is used to organize data into useful categories, or in other words, transform data into
Determine the Research Direction
Collection and Organization of cost-influencing factors Interview with experts (Group 1)
Literary Review
Organize the factors using the KJ method Design the first round of questionnaire
MDM 2 -group and 2 -round Questionnaire Group 1
Group 2
First round
First round
Questionnaire Analysis
Questionnaire Analysis
Design the second round of questionnaire
Design the second round of questionnaire
Second round
Second round
Questionnaire Analysis Filter the key factors Rank the key factors Conclusion and Recommendations
Fig. 1. Research process.
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information (Lance, 2006). Zaphiris et al. (2005) employed the KJ method to study a set of age-centered and research-based web design guidelines. Cheng and Leu (2011) integrated data mining with the KJ method to analyze bridge construction defects. To create an affinity diagram, a group of people, index cards or sticky notes, and a physical space are required. The steps in the KJ method are as follows: (1) determine the theme; (2) gather the data; (3) sort the data into groups; (4) create header cards, and (5) draw the finished diagram. In step (3), people first transfer the data onto the index cards or sticky notes, scatter the cards on a table or post the notes on a wall, and then arrange the cards according to related ideas, issues, or topics of data (Plain, 2007). The factors collected during the initial stage come from different experts and literatures and may be interrelated or with similar wording. The KJ method may effectively filter and consolidate the factors into independent factors for the use of follow-up questionnaires. 4.2. Modified Delphi Method The Delphi concept was developed by the American defense industry (Chan et al., 2001). Its characteristics include anonymity, iteration with controlled feedback and statistical response (Yeung et al., 2009). It collects the opinions of the experts in the related field through questionnaire to deal with complex issues. To keep the experts from influencing each other's opinions, the traditional Delphi utilizes one to several rounds of questionnaires anonymously. The most significant drawback is that the reiterations are time-consuming. Murry and Hammons (1955) modified the Delphi method based on special considerations. They omit the complex process of open questionnaire and replace the first round of questionnaire with literary exploration or interviews with the experts. Besides, there are innumerable applications for the Delphi method in recent years. Chan et al. (2001) used the criteria and utility factors derived from the Delphi survey technique to develop a multi-attribute procurement selection model. Yeung et al. (2009) applied the Delphi survey technique with four rounds of questionnaires with 22 experts from the construction industry to formulate a model to assess the success of relationship-based construction projects in Australia, and eight key performance indicators were selected. Hallowell and Gambatese (2010) explored the application of the Delphi method in Construction Engineering and Management (CEM), which consists of some of the researches that are applied toward CEM with recommendations on the procedures of the traditional Delphi and parameters for each stage. Ma et al. (2011) adopted the Fuzzy Delphi method and Grey Delphi method to construct three sets of road safety performance indicators. The above-mentioned Delphi applications all received decent results. In addition, the process of arriving at the cost-influencing factors from the open questionnaire is complex and difficult during the initial stage of traditional Delphi. Existing studies on similar subject matters provide ample references for this study. Many of those on the subject of cost-influencing factors adopt literary review and interview with experts to identify the factors in the initial stage (Dissanayaka and Kumaraswamy,
1999; Elhag et al., 2005; Elinwa and Buba, 1993). Considering the limited resources and weighing in the value of existing studies to this research, it seems more feasible to modify the first round of traditional Delphi (MDM) instead of that with an open-ended questionnaire and starting from scratch. Therefore, MDM (Murry and Hammons, 1955) is adopted for this study. In addition, this study is built on the foundation of existing studies to be on the cautious side and thus adopts the approach of identifying the cost-influencing factors from the literatures supplemented with interviews with experts.
5. Collection and organization of cost-influencing factors At this stage, according to the first stage of MDM, literary review (Dissanayaka and kumaraswamy, 1999; Elhag et al., 2005; Elinwa and Buba, 1993; Kaming et al., 1997; Shane et al., 2009) and individual interviews are conducted with engineers from various construction companies to identify the initial cost-influencing factors. Besides, the KJ method is also applied to help organize these factors and develop them for the questionnaire for the later stages. Chan et al. (2001) once stressed that the success of Delphi lies in the careful selection of the panel members. In order to identify eligible participants for the current Delphi study and to appropriately reflect the current conditions of the construction company, the following three criteria were devised: (1) practitioners having extensive working experience in cost control; (2) experts having a sound knowledge and understanding of cost control concepts in the construction companies; and (3) experts having current, recent or direct involvement in the management of cost control in the construction companies. Therefore, all panel members selected for this study were once or are currently employed in the Grade A comprehensive construction enterprises (with a capital over NT$225 millions) in Taipei, Taiwan. They include cost control managers and senior engineers who are involved in the cost control process, among which 1 has over 20 years of experience, 3 with 10 to 20 years of experience, and 8 with 5 to 10 years. According to Hallowell and Gambatese (2010), most studies incorporate 8 and 16 panelists while a minimum of 8 is recommended and 12 are selected, which is within the reasonable range. 90 initial cost-influencing factors are compiled at this stage. They are further consolidated into 42 factors under 4 categories with KJ method. The KJ processes are discussed by the researcher and some of the experts of Group 1. For example, in Fig. 3, user demand, structure type, project type and project location are factors that are relevant to each other. Therefore, scale of construction is used instead of these 4 factors. Project scope specified in the bid belongs to clearly define the scope of project in the contract, so they are combined as one factor. All of the factors: scale of construction, clearly define the scope of project in the contract, contract types, and so on are all related to contract scope, so the factor, Scope of Contract is used instead. According to the organization by the KJ processes, the results are shown in Figs. 2–5, the category of “Environmental and Circumstantial Influence” includes 8 factors, “Scope of Contract” includes 8,
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Environmental and circumstantial influence
Interest rate on bank loans
The fluctuations in labor cost is too great Natural disaster
Changes in mortgage rates
Climate factor
Political environment The fluctuations in commodity price is too great
Geology, topography
The real estate prospect
Gross domestic products (GDP)
Fig. 2. Affinity diagram for environmental and circumstantial influence.
“Project Risks” contains 10, and “Management and Technique” contains 16 factors.
Group 2 is no longer being employed in the construction companies. The purpose is to compare and verify the views and perspectives between members working in the construction company (Group 1) and those who do not (Group 2). 5 panel members in Group 2 have over 20 years of experience, 3 with 10 to 20 years of experience, and 3 with 5 to 10 years of experience, a total of 11 members. The questionnaire assigns a five-point Likert scale to each of the 42 factors under the 4 categories. Separate surveys were conducted for Group 1 and Group 2 where 12 questionnaires were sent to Group 1 and 11 to Group 2. The results of the first round of questionnaire are shown in Tables 1.1 to 1.4. The means from Group 1 and Group 2 for the first round are used as the feedback for the second round of questionnaires and shown to the panel members so that they can quickly reach consensus according to the significance of the factors. The analysis of the feedback is shown in Tables 2.1 to 2.4, in which the mean values for Group 1 and Group 2 for each of the 4 categories are quite close.
6. Analysis and ranking of cost-influence factors 6.1. Modified Delphi Method with 2 groups and 2 rounds There are 2 groups of recipients for the questionnaire and 2 rounds of questionnaires were conducted to obtain the key factors. The panel members for one of the groups are those from whom the 90 initial factors were obtained (Group 1). To cross-reference the influence of these factors during construction, another group of experts (Group 2) with no involvement in selecting the factors in the initial stage were chosen for the two rounds of MDM. Group 2 consists of engineering staff or officials who are involved in cost control. 3 of them are employed in the public sector, 6 are employed in the consulting firms, and 2 in the construction companies. The emphasis for
Scope of of contract contract The level of demand on quality
Contract types
Modifications of project schedule ( ahead of schedule or stop in mid -construction )
Project quality Contract dispute (unclear drawings or guidelines/regulations) Modifications to the scope of construction
Clearly define the scope of project in the contract
The client applies/requests for modifications
Project scope specified in the bid
Scale of construction
The types of clients
User demand
Structure type
The client's way of dealing with key decisions
Project type
Project location
The client asks that the project be done ahead of schedule
Fig. 3. Affinity diagram for scope of contract.
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Project risks Project risks Protest
Stagnant project
Neighbor protests
Policy change
Tilted neighboring structure
Delayed procurement
Unexpected technical difficulties
Labor protests
Disputes in opinions over the construction drawings The project scale is too big and the project itself too complex
Inadequate construction techniques Material shortage or supply delay
The client's financial capability
Design modifications
The subcontractors bankrupted
Occupational hazards
Inadequate project listing Add new construction activities Add on to the number of activities
The gap between the construction plan and the reality is too great
Fig. 4. Affinity diagram for project risks.
Management and Technique Time management
Project control meeting
Material management
Monitor and feedback
The timetable for the materials to be delivered on site
Arrangement of construction progress
The understanding of operational procedures during project management
Project valuation does not match the collected payment
The client and engineer understand the difficulties in the actual operation and made appropriate decisions
Procurement contract
The order of construction projects
Subcontractor's valuation
Regular budget update
Cost control
Personnel training Project manager's capability Budget exceptions
Labor attendance
Project manager's leadership project manager's understanding of the operational procedure
Whether the high-level management decentralizes the power Project team (coordination capability and the understanding of operational procedure) Interactions among the project participants
Coordination among the team members
Project manager's practical experience Job site safety and health management Project manager's coordination capability Carry out supervision Project manager's risk management ability
Whether the monitoring is implemented Coordination and mutual understanding among the high-level management
Team work among the subcontractors
Coordination between the project manager and the high-level management Conflicts that occur while the high-level management manages the project
Practical experience the lack of experience for this type of project
Construction methods
Subcontractors' construction techniques
Construction machinery and equipment
Subcontractors' financial difficulties
Replacement of construction equipment
Support from the high-level management Terminate the contractor's contract and re-issue the contract Coordination between the project manager and subcontractors Attitudes of the project manager and the subcontractors Subcontractors' passive attitude toward project management
Knowledge and experience Bid rigging
Quality of the labor and engineering staff Competitive bidding Construction personnel's real-time decision-making
Fig. 5. Affinity diagram for management and technique.
Bid preparation period
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Table 1.1 First round results — environmental and circumstantial influence.
6.2. Analysis
Factor
To further identify the significant cost-influencing factors among the 42 known factors, the ones that fall out of the measures of central tendency or with a measure of variation that's too great are excluded. The qualifications include: (1) the mean of the single factor is greater than 3 and larger than the mean of the factors within that category; (2) the quartile range is equal to or less than 0.5; and (3) the standard deviation of the single factor is equal to or less than 1. Table 3 shows factors from both Groups 1 and 2 that meet all three of the above mentioned qualifications. There are 4 factors each under the categories of Environmental and Circumstantial Influence and Scope of Contract, 2 under Project Risks, and 6 under Management and Technique. The radar charts in Figs. 6 to 8 show the comparison of the mean, standard deviation and quartile ranges between the 2 groups. In terms of the mean (as shown in Fig. 6), the two groups hold opposite views toward factor A-4, High Fluctuations in Commodity Price. The mean from Group 1 is 4.92 with a standard deviation of 0.3 and a quartile range of 0. Among the 12 panel members, 11 gave the maximum value of 5, and only 1 gave 4. A reasonable explanation would be that the construction companies often have to absorb the changes in cost as a result of fluctuating commodity price. Therefore, 11 members held the same view
Group 1
Group 2
Mean Standard Quartile Mean Standard Quartile deviation ranges deviation ranges Climate factor Natural disaster Geology, Topography Political environment High fluctuation in labor cost High fluctuation in commodity Gross domestic products (GDP) Interest rate on bank loans Average
4.00 4.00 4.42
1.10 0.70 0.80
0.60 0.30 0.50
4.09 4.09 4.18
0.70 0.8 0.6
0.30 0.8 0.3
2.92 3.83
0.80 0.90
0.10 0.60
3.64 3.55
1.2 0.8
1.3 0.5
4.58
0.50
0.50
4.55
0.5
0.5
3.58
0.90
0.50
3.27
1.1
0.8
3.67
0.90
0.60
3.82
0.9
0.8
3.88
0.83
0.46
3.90
0.83
0.66
Therefore, it can be concluded that the perspective of the construction company match that of the client. The Scope of Contract and Project Risks are the two categories with higher influences on project costs. In contrast, the influence of the Environmental and Circumstantial factors is relatively low.
Table 1.2 First round results — scope of contract. Factor
Clearly define the scope of project in the contract Scale of construction The types of clients Contract types Modifications to the scope of construction Modifications of project schedule (ahead of schedule or stop in mid-construction) Contract dispute (unclear drawings or guidelines/regulations) The level of demand on quality Average
Group 1
Group 2
Mean
Standard deviation
Quartile ranges
Mean
Standard deviation
Quartile ranges
4.75 3.33 3.75 3.83 4.33 4.58
0.40 0.90 0.70 0.80 0.60 0.50
0.10 0.50 0.10 0.10 0.50 0.50
4.55 3.73 3.82 3.82 4.09 4.09
0.7 0.7 0.7 0.7 0.9 0.5
0.5 0.3 0.5 0 1 0
4.58 4.42 4.20
0.50 0.60 0.63
0.50 0.50 0.35
4.45 4.09 4.08
0.5 0.9 0.70
0.5 0.5 0.41
Table 1.3 First round results — project risks. Factor
Group 1
Group 2
Mean
Standard deviation
Quartile ranges
Mean
Standard deviation
Quartile ranges
Design modifications Protest The client's financial capability Stagnant project Occupational hazards Inadequate project listing The vendors/contractors/subcontractors went bankrupted Inadequate construction techniques The gap between the construction plan and the reality is too great. Material shortage or supply delay Average
4.33 3.75 4.42 4.42 4.67 4.17 3.75 4.08 4.42 4.58 4.26
0.70 0.70 0.60 0.50 0.50 0.70 0.60 0.80 0.80 0.60 0.65
0.50 0.50 0.50 0.50 0.50 0.50 0.50 0.60 0.50 0.50 0.51
3.91 4.55 3.91 4.00 4.45 4.00 4.36 4.55 4.45 4.73 4.29
0.9 0.7 0.8 0.6 0.5 0.9 0.9 0.5 0.7 0.6 0.71
0.5 0.5 0 0 0.5 0.3 0.5 0.5 0.5 0 0.33
856
Y.-M. Cheng / International Journal of Project Management 32 (2014) 850–860
Table 1.4 First round results — management and technique. Factor
Group 1
Cost control Project control meeting Labor attendance Carry out supervision/monitoring Project valuation does not match the collected payment. Whether the high-level management decentralizes the power. Staff/personnel training Regular budget update Job site safety and sanitation/health management Budget exceptions Material management Practical experience Procurement contract Time management The project manager's capability Project team (coordination capability and the understanding of operational procedure) Average
Group 2
Mean
Standard deviation
Quartile ranges
Mean
Standard deviation
Quartile ranges
4.75 4.00 3.67 4.17 4.08 4.50 4.08 3.75 4.33 3.83 4.17 4.33 4.50 4.50 4.67 4.58
0.40 0.70 0.70 0.70 0.60 0.50 0.60 1.00 0.90 0.70 0.60 0.50 0.50 0.50 0.50 0.50
0.10 0.30 0.50 0.50 0.10 0.50 0.10 0.60 1.00 0.50 0.10 0.50 0.50 0.50 0.50 0.50
4.64 4.18 3.91 4.18 4.36 4.09 3.91 4.09 3.91 3.91 4.18 4.64 4.18 4.18 4.36 4.45
0.5 0.6 0.7 0.6 0.9 0.7 0.8 0.8 0.5 0.5 0.8 0.5 1.1 0.7 0.9 0.7
0.5 0.3 0 0.3 0.5 0.3 0 0.3 0 0 0.5 0.5 0.5 0.5 0.5 0.5
4.24
0.62
0.43
4.21
0.72
0.34
and gave the rating of 5. The mean for Group 2 is 4.00 with a standard deviation of 0.7 and a quartile range of 0.5. 3 of the 11 panel members gave the maximum value of 5, and 3 gave the value of 3. Members in Group 2 are from different sectors. Although they each hold a different view, with a mean of 4.00,
the group still thinks that factor A-4 holds certain influence over construction costs. Figs. 7 and 8 show the comparison of the standard deviation and quartile range between the two groups. It is shown that the standard deviation for factor C-2 from Group 1, Material Shortage or Supply Delay, is 0.9, the
Table 2.1 Second round results — environmental and circumstantial influence. Factor
Climate factor Natural disaster Geology, topography Political environment High fluctuation in labor cost High fluctuation in commodity price Gross domestic products (GDP) Interest rate on bank loans Average
Group 1
Group 2
Mean
Standard deviation
Quartile ranges
Mean
Standard deviation
Quartile ranges
4.00 3.75 4.33 3.00 3.33 4.92 3.00 3.67 3.75
0.60 0.4 0.6 0.7 0.7 0.3 0.6 0.7 0.58
0.00 0.1 0.5 0.3 0.5 0 0 0.5 0.24
4.27 4.27 4.09 3.55 3.36 4.00 3.18 3.55 3.78
0.40 0.4 0.7 0.8 0.6 0.7 0.7 0.7 0.63
0.30 0.3 0.3 0.5 0.5 0.5 0.5 0.5 0.43
Table 2.2 Second round results — scope of contract. Factor
Clearly define the scope of project in the contract Scale of construction The types of clients Contract types Modifications to the scope of construction Modifications of project schedule (ahead of schedule or stop in mid-construction) Contract dispute (unclear drawings or guidelines/regulations) The level of demand on quality Average
Group 1
Group 2
Mean
Standard deviation
Quartile ranges
Mean
Standard deviation
Quartile ranges
4.83 3.33 3.83 3.58 4.25 4.08
0.4 0.6 0.8 0.9 0.6 0.6
0 0.5 0.1 0.5 0.5 0.1
4.64 3.64 3.64 3.55 4.45 4.36
0.5 0.8 0.6 0.7 0.7 0.6
0.5 0.5 0.5 0.5 0.5 0.5
4.83 4.42 4.15
0.4 0.6 0.61
0 0.5 0.28
4.45 4.27 4.13
0.7 0.9 0.69
0.5 0.5 0.50
Y.-M. Cheng / International Journal of Project Management 32 (2014) 850–860
857
Table 2.3 Second round results — project risks. Factor
Group 1
Design modifications Protest The client's financial capability Stagnant project Occupational hazards Inadequate project listing The vendors/contractors/subcontractors went bankrupted Inadequate construction techniques The gap between the construction plan and the reality is too great. Material shortage or supply delay Average
Group 2
Mean
Standard deviation
Quartile ranges
Mean
Standard deviation
Quartile ranges
4.33 3.33 4.67 4.17 4.75 4.08 3.33 3.92 4.33 4.33 4.13
0.6 0.6 0.5 0.9 0.4 0.8 0.9 0.5 0.7 0.9 0.68
0.5 0.1 0.5 0.5 0.1 0.6 0.5 0 0.5 0.5 0.38
3.91 4.45 3.82 4.18 4.00 3.82 4.00 4.55 4.64 4.64 4.20
0.9 0.5 0.6 0.6 0.7 0.7 0.9 0.8 0.6 0.6 0.69
0.5 0.5 0.3 0.3 0.5 0 0.3 0.3 0.3 0.3 0.33
quartile range is 0.5 and the mean is 4.33. Also, 7 of the 12 members gave the rating of 5, and only 1 member gave the rating of 2. Therefore, it is determined that this factor should be considered a main cost-influencing factor. In addition, the figures also show that the standard deviation of factor B-4 from Group 2, The Level of Demand on Quality, is 0.9, and the mean is 4.27. 5 of the 11 members rated it 5 and only 1 member rated it 2. Therefore it is also considered a main cost-influencing factor. After summarizing the analysis from the MDM with 2 groups and 2 rounds, 16 key cost-influencing factors were identified.
Shash (1993) recommended this method for the analysis of ordinal data collected through the Likert scale. Elhag et al. (2005), Chan (2012), Rahman et al. (2013), and Olawale and Sun (2013) also used the same approach. The SI is as follow: ! 5 X 100% SI ¼ ð1Þ wi f i n i¼1 where i represents the ratings 1–5, fi is the frequency of responses, n is the total number of responses, and wi is the weight for each rating: i A
ð2Þ
6.3. Ranking result
wi ¼
To rank the 16 key factors, the second round of the questionnaires was sent to the 23 panel members in both groups. Then Severity Index (SI), also known as Relative Importance Index (RII) was adopted to rank the cost factors.
where A is the highest score (i.e. 5 in this case). The rankings of the means of SI for the 4 categories are shown in Table 3. It is evident that the Scope of Contract and Project Risks are the two categories that pose higher influences over project costs. In
Table 2.4 Second round results — management and technique. Factor
Cost control Project control meeting Labor attendance Carry out supervision/monitoring Project valuation does not match the collected payment. Whether the high-level management decentralizes the power. Staff/personnel training Regular budget update Job site safety and sanitation/health management Budget exceptions Material management Practical experience Procurement contract Time management The project manager's capability Project team (coordination capability and the understanding of operational procedure) Average
Group 1
Group 2
Mean
Standard deviation
Quartile ranges
Mean
Standard deviation
Quartile ranges
4.83 3.92 3.25 3.83 4.08 4.08 3.50 3.50 4.00 3.58 4.17 4.50 4.42 4.50 4.42 4.42
0.4 0.3 0.4 0.6 0.6 0.8 0.6 1 0.7 1 0.6 0.6 0.6 0.6 0.6 0.6
0 0 0.1 0.1 0.1 0.6 0.5 0.5 0.3 0.6 0.1 0.5 0.5 0.5 0.5 0.5
4.64 4.00 3.55 3.82 4.55 4.09 3.73 4.00 3.82 3.55 3.91 4.27 4.09 4.36 4.00 4.27
0.5 0.7 0.7 0.7 0.5 0.8 0.7 0.6 0.9 0.5 0.3 0.4 0.5 0.5 1 0.6
0.5 0.5 0.5 0 0.5 0.3 0.3 0 0.8 0.5 0 0.3 0 0.5 0.8 0.5
4.08
0.62
0.35
4.05
0.62
0.38
858
Y.-M. Cheng / International Journal of Project Management 32 (2014) 850–860 A-1
Table 3 Mean SI for the categories with key cost — influencing factors. Category
D-6
Factor
terms of the rankings for the individual factors (as shown in Table 4), Clearly Defined Scope of Project in the Contract and Cost Control are the most important cost impact factors with 94.78. The second highest is Contract Dispute with 93.04, which clearly makes it a significant factor. If the contract does not clearly delineate the scope of project, or if the construction drawings are unclear with ambiguous specifications, expectations from both parties may differ and cause unnecessary disputes after the construction commences. In addition, price fluctuation is another main factor for cost overruns. For projects of a larger scale or with longer construction periods, it is vital to understand the fluctuations in prices in recent years and the acceptable level of fluctuation. The construction companies should examine whether the contract contains stipulations on adjustments for price index. Price fluctuation should also be monitored regularly and reflected to the clients. Finally, although
5.00
D-4
0.40
D-3
B-1
D-2 D-1
B-3 C-2
B-4 C-1
Fig. 7. Radar chart for standard deviation comparison between the two groups.
Geology, Topography, Climate Factors, and Natural Disasters are the lowest ranking factors, they are still selected among the 46 initial factors and have a certain degree of influence over project costs. 6.4. Case study Construction projects are large scale in nature. They involve long project period, and each is distinctive and complex in its own way. In addition, the clients and contractors' abilities are also at play, which may affect the project positively or negatively. The factors may also be in any form. For example, the regional requisition for Taiwan High Speed Rail station covers a geographic area of 141.48 ha. The public construction project involves grading, road improvement, drainage, public lighting, transportation infrastructure, sewage, irrigation and plant relocation. The project also involves common duct projects and utility contracting projects. The contract stipulated that the total cost for the project was NT$1,126,867,413 and the project period was 1060 calendar days, the final project cost was NT$ 1,116,204,121, a decrease of NT$10,663,292 (LCEB,
A-2
0.50
A-2
0.40
D-5
A-3
A-3
0.30 D-4
A-4
0.20
A-4
0.10
1.00
Group 1
0.00
B-1
D-2 D-1
Group 1
0.00
D-3
B-1
Group 2
B-2 B-3 C-2
Group 2
B-2
D-6
2.00
D-3
Group 1
0.00
3.00 D-4
A-4
0.20
A-1
4.00
D-5
A-3
0.60
A-1 D-6
A-2
0.80
D-5
Environmental and circumstantial 1. Climate factor influence (A) 2. Natural disaster (SI = 84.13) 3. Geology, Topography 4. High fluctuation in commodity Scope of contract (B) 1. Clearly define the scope of project in (SI = 90.44) the contract 2. Modifications to the scope of construction 3. Contract dispute (unclear drawings or guidelines/regulations) 4. The level of demand on quality Project risks (C) 1. The gap between the construction plan (SI = 89.57) and the reality is too great 2. Material shortage or supply delay Management and technique (D) 1. Cost control (SI = 88.26) 2. Project valuation does not match the collected payment 3. Practical experience 4. Procurement contract 5. Time management 6. Project team (coordination capability and the understanding of operational procedure)
1.00
B-4 C-1
Fig. 6. Radar chart for mean comparison between the two groups.
D-2
Group 2
B-2 B-3
D-1 C-2
B-4 C-1
Fig. 8. Radar chart for quartile range comparison between the two groups.
Y.-M. Cheng / International Journal of Project Management 32 (2014) 850–860 Table 4 Ranking of the key cost — influencing factors. N0
Factor
7. Conclusion SI Rank (Severity Index)
B-1 Clearly define the scope of project in the contract D-1 Cost control B-3 Contract dispute (unclear drawings or guidelines/regulations) A-4 High fluctuation in commodity C-1 The gap between the construction plan and the reality is too great C-2 Material shortage or supply delay D-5 Time management D-3 Practical experience B-2 Modifications to the scope of construction B-4 The level of demand on quality D-6 Project team (coordination capability and the understanding of operational procedure) D-2 Project valuation does not match the collected payment D-4 Procurement contract A-3 Geology, topography A-1 Climate factor A-2 Natural disaster
859
94.78
1
94.78 93.04
1 2
89.57 89.57
3 3
89.57 88.70 87.83 86.96 86.96 86.96
3 4 5 6 6 6
86.09
7
85.22 84.35 82.61 80.00
8 9 10 11
2004). This is a successful case of cost control. Overall, the contract for this project clearly defines the scope and the project costs are well controlled. However, this project involves huge amount of capital and a vast number of factors are at play. Therefore, only public construction projects and common duct projects with greater variations in costs are used for this case study. Table 5 shows the effects of major cost-influencing factors for each aspect and the costs involved. It also indicates that the factors identified in this study agree with those from actual practice. It confirms that the final costs are closely associated with how well the factors are controlled. In additional note, though project costs were affected by the typhoon and inflation, they are within the scope of anticipated burden of risks (LCEB, 2005).
Many literatures and actual projects indicate that construction cost overrun is a common problem in the construction field. Identifying the cost-influencing factors is the first step toward addressing such problem. If construction companies can effectively control these key factors and formulate prevention strategies, it is possible not only to avoid cost overrun, but also to increase the overall profits for the project. In order to factually provide the key cost-influencing factors to the construction companies, the cost-influencing factors are analyzed and discussed from the perspectives of the construction companies. The KJ method and MDM with 2 groups and 2 rounds are utilized to improve the traditional Delphi method, and Severity Index (SI) computation was adopted to rank the factors. According to the result of the SI, the highest to the lowest categories are Scope of Contract, Project Risks, Management and Technique, and Environmental and Circumstantial Influence. There are 16 key cost-influencing factors in these 4 categories. Factors with the strongest influence include Clearly Define the Scope of Project in the Contract, Cost Control and Contract Dispute. In practice, construction companies must clearly understand the client's needs through communication during the initial stage of the project. They must have clear understanding of the scope of the contract and ask the clients for necessary clarifications regarding the drawings and specifications prior to signing the contract to avoid pricing disputes. Additionally, during project implementation, the contractors should fully implement cost-control measures. Construction companies can also use the remaining factors to conduct a thorough investigation that is tailored to the characteristics of the project and the client prior to the project commences in order to minimize uncertainties and reduce the chance of cost overruns. Abbreviations CEM Construction Engineering and Management KJ Kawakita Jiro method, affinity diagram MDM Modified Delphi Method
Table 5 Effect of cost-influencing factors on public construction and common duct projects. Category
Contract stipulated costs (NT$)
Increase/ Details (factors) decrease (NT$)
Public construction project
740,870,943
− 8,520,717
Common duct project
186,310,553
3,376,191
1. For items whose actual quantities cannot be confirmed during the planning and design stage, the contract stipulated that the payment schedule is based on actual completion. Examples include grit chambers, road pavement and compressed concrete paving units, which were significantly reduced from the original estimate. (B-1) 2. Fully implement cost control and regularly review the required quantity and construction costs. (D-1) 1. Contract omissions. (B-3) 2. Design changes due to site conditions. (B-2, C-1) 3. Unfamiliarity with local culture, which affected the design of the manhole cover. The client intervened later on for the redesign. (C-1) 4. The drilling indicated inconsistency with current conditions. Additional backfill required. (C-1) 5. Poor control over the transfer schedule and unclearly defined responsibility resulted in theft finished installations. (D-5, D-6) 6. Project redo due to poor construction quality. (B-4)
860
RII SI
Y.-M. Cheng / International Journal of Project Management 32 (2014) 850–860
Relative Importance Index Severity Index
Acknowledgments The author would like to thank all participating experts, especially Kuang-Hu Cheng, former worksite director of Land Consolidation Engineering Bureau and Yu-Ming Liu, senior engineer with CECI Engineering Consultants, without their valuable contributions this research would not have been possible. Moreover, the authors would like to acknowledge the reviewers for contributing helpful suggestions and insightful comments, which greatly improved the quality of this paper. References Chan, C.T.W., 2012. The principal factors affecting construction project overhead expenses: an exploratory factor analysis approach. Constr. Manage. Econ. 30 (10), 903–914. Chan, A.P.C., Yung, E.H.K., Lam, P.T.I., Tam, C.M., Cheung, S.O., 2001. Application of Delphi method in selection of procurement systems for construction projects. Constr. Manage. Econ. 19 (7), 699–718. Chang, A.S., 2002. Reasons for cost and schedule increase for engineering design projects. J. Manage. Eng. 18 (1), 29–36. Chen, J.H., Hsu, S.C., 2008. Quantifying impact factors of corporate financing: engineering consulting firms. J. Manage. Eng. 24 (2), 96–104. Cheng, Y.M., Leu, S.S., 2011. Integrating data mining with KJ method to classify bridge construction defects. Expert Syst. Appl. 38 (6), 7143–7150. Dissanayaka, S.M., Kumaraswamy, M.M., 1999. Evaluation of factors affecting time and cost performance in Hong Kong building project. Eng. Constr. Archit. Manage. 6 (3), 287–298. Doloi, H.K., 2011. Understanding stakeholders' perspective of cost estimation in project management. Int. J. Proj. Manage. 29, 622–636. Doloi, H., 2013. Cost overruns and failure in project management: understanding the roles of key stakeholders in construction projects. J. Constr. Eng. Manage. 139 (3), 267–279. Elhag, T.M.S., Boussabaine, A.H., Ballal, T.M.A., 2005. Critical determinants of construction tendering costs: quantity surveyors standpoint. Int. J. Proj. Manage. 23, 538–545.
Elinwa, A.U., Buba, S.A., 1993. Construction cost factors in Nigeria. J. Constr. Eng. Manage. 119 (4), 698–713. Flyvbjerg, Bent, Holm, Skamris, Mette, K., Buhl, Soren L., 2002. Underestimating costs in public works projects: error or lie? J. Am. Plan. Assoc. 68 (3), 279–295. Hallowell, M.R., Gambatese, J.A., 2010. Qualitative research: application of the Delphi method to CEM research. J. Constr. Eng. Manage. 136 (1), 99–107. Kaming, P.F., Olomolaiye, P.O., Holt, G.D., Harris, F.C., 1997. Factors influencing construction time and cost overruns on high-rise projects in Indonesia. Constr. Manage. Econ. 15, 83–94. Lance, D., 2006. Creating an Affinity Diagram. LL Decker Associates, Inc.(Helping organizations change). LCEB, 2004. Land Consolidation Engineering Bureau, Ministry of the Interior, Expense Report, Regional Requisition for Taiwan High Speed Rail Taoyuan Station. LCEB, 2005. Land Consolidation Engineering Bureau, Ministry of the Interior, Evaluation Report, Regional Requisition for Taiwan High Speed Rail Taoyuan Station. Love, P.E.D., Wang, X., Sing, C.P., Tiong, R.L.K., 2013. Determining the probability of project cost overruns. J. Constr. Eng. Manage. 139 (3), 321–330. Ma, Z., Shao, C., Mac, S., Ye, Z., 2011. Constructing road safety performance indicators using Fuzzy Delphi method and Grey Delphi method. Expert Syst. Appl. 38, 1509–1514. Murry, J.W., Hammons, J.O., 1955. Delphi: a versatile methodology for conducting qualitative research. Rev. High. Educ. 18 (4), 423–436. Olawale, Y., Sun, M., 2013. PCIM: project control and inhibiting-factors management model. J. Manage. Eng. 29 (1), 60–70. Plain, C., 2007. Build an affinity for KJ method. Qual. Prog. 40 (3), 88. Rahman, I.A., Memon, A.H., Karim, A.T.A., 2013. Significant factors causing cost overruns in large construction projects in Malaysia. J. Appl. Sci. 13 (2), 286–293. Shane, J.S.A., Molenaar, K.R., Anderson, S., Schexnayder, C., 2009. Construction project cost escalation factors. J. Manage. Eng. 25 (4), 221–229. Shash, A.A., 1993. Factors considered in tendering decisions by top UK contractors. Constr. Manage. Econ. 11 (2), 111–118. Yeung, J.F.Y., Chan, A.P.C., Chan, D.W.M., 2009. Developing a performance index for relationship-based construction projects in Australia: Delphi study. J. Manage. Eng. 25 (2), 59–68. Zaphiris, P., Ghiawadwala, M., Mughal, S., 2005. Age-centered Researchbased Web Design Guidelines. Portland, Oregon, USA.