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Improving sub-contractor selection process in construction projects: Web-based sub-contractor evaluation system (WEBSES)
Automation in Construction 17 (2008) 480 – 488 www.elsevier.com/locate/autcon
Improving sub-contractor selection process in construction projects: Web-based sub-contractor evaluation system (WEBSES) Gokhan Arslan a,⁎, Serkan Kivrak a , M. Talat Birgonul b , Irem Dikmen b a
b
Anadolu University, Civil Engineering Department, 26555 Eskisehir, Turkey Middle East Technical University, Civil Engineering Department, 06531 Ankara, Turkey Accepted 14 August 2007
Abstract One of the most important phases in the construction industry (CI) is the bidding process. During the bidding process, selecting the most appropriate sub-contractors (SCs) for the relevant sub-works is highly critical for the overall project performance. In order to select the most appropriate SCs for the project and prepare the most realistic and accurate bid proposal, general contractors (GCs) have to know all financial, technical and general information about these SCs. Within this context, GCs should consider several factors in the selection process. These factors may include the quality of production, efficiency, employment of qualified members, reputation of the company, accessibility to the company, completion of the work on time etc. This paper proposes a web-based sub-contractor evaluation system called WEBSES by which the SCs can be evaluated based on a combined criterion. It enables GCs to select the most appropriate SCs for their relevant sub-works, speed up the selection process and gain time and cost savings during the bidding process. © 2007 Elsevier B.V. All rights reserved. Keywords: Sub-contractor; Construction industry; Information technology (IT); Evaluation
1. Introduction Sub-contracting has extensively been used in the CI. It allows GCs to employ a minimum workforce in construction projects and promotes specialization [1,2]. Many GCs only act as construction management agents in construction projects and sub-contract a large volume of their work to SCs [3]. SCs play an important role in the success of construction projects [4,5]. The success level of these projects may depend on the philosophy of selecting “the right person for the right job” [6]. Clearly, the correct choice of SCs increases the overall success of a construction project. However, the importance of SC selection is mostly underestimated and neglected in construction [7,8]. SC evaluation is a vital part of the project management cycle. As construction projects become more complex, the need for
⁎ Corresponding author. Tel.: +90 222 321 35 50; fax: +90 222 323 95 01. E-mail addresses: [email protected] (G. Arslan), [email protected] (S. Kivrak), [email protected] (M.T. Birgonul), [email protected] (I. Dikmen). 0926-5805/$ - see front matter © 2007 Elsevier B.V. All rights reserved. doi:10.1016/j.autcon.2007.08.004
evaluating SC performance becomes more crucial. Although there are no generalized sets of rules in evaluating SCs, several factors should be considered by the GC in the selection process. These factors may include the quality of production, efficiency, employment of qualified members, reputation of the company, accessibility to the company, completion of the work on time, etc. The use of information technology (IT) applications in the CI has been recognized as highly essential for improving business performance [9,10]. IT tools enable companies to speed up the business activities. Especially, Internet-based technology has been recognized as the most important tool to facilitate information transfer effectively and a collaborative working environment in construction projects [11]. A considerable amount of time and cost saving can be achieved by the use of Internet technologies. A construction company has generally several projects that are located in different geographical areas. Information exchange can be performed effectively between the members of these projects through the use of web-based applications. Thus, problems caused by geographic fragmentation can significantly be reduced [12]. When considered the advantages, the use of web-based technology can be an effective
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way in the SC evaluation process. This paper presents a webbased sub-contractor evaluation system called WEBSES by which the SCs can be evaluated based on a combined criterion. GCs can select the most appropriate SCs for their relevant subworks, speed up the selection process and gain the advantage of saving time and cost during the bidding process through this system. 2. Bidding process in the construction industry Bidding for construction projects is a critical decision for construction companies. It is especially crucial for international construction projects by which the companies aim to position themselves in the international construction market [13]. The bidding process is also a critical task in the construction industry. The amount of profit level is critically determined at this stage. Since the major objective of the construction companies is to expand business volume by successful bidding on various projects, preparing realistic and accurate bid proposals is the most significant component for the expansion. The bidding process in the CI is characterized by the involvement of many different parties including the client, architectural and engineering firms, GCs, specialized contractors, material suppliers, manufactur ers, etc [14]. Preparing tender documents, evaluating bids, and
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awarding the contract to the winner of the bid are among the major duties of the client. The GCs also follow the same sequential procedure for the selection of their SCs [15]. Construction company's bidding strategies change according to bidding system, client, country and bid evaluation criteria [16]. The methods of preparing bid proposals for construction projects also vary according to the structure and characteristics of the project. The bidding process requires a great deal of time and effort especially for complex projects. Therefore, a systematic procedure should be followed to prepare bid proposals for such projects. In Fig. 1, the necessary phases that should be followed for bid proposal preparation are illustrated. It should be noted that these phases are summarized according to the traditional approach of the bidding process, that is, without using the latest technologies such as e-bidding. It should also be considered that any omitted item in these phases would cause delays or mistakes in the bidding process. 3. Sub-contractor selection in the bidding process In the CI, biddings usually occur between GCs and SCs. GCs rely mostly on the bid prices submitted by the SCs to estimate the final bid sum for the projects. Thus, SCs play an important role in the bidding process. During the bidding process, selecting the
Fig. 1. Phases during a typical bidding process.
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most appropriate SCs for the sub-works is highly critical. Therefore, GCs must be extremely careful while selecting the most appropriate SC for a certain part of the work or the entire project [15]. They have to be fair and objective in their relations with the SCs. Poor selection of SCs may lead to the elimination of qualified SCs from business or result in a lowering of their standards, thus, producing cheap and poor quality work [3]. Also the GCs may loose time and money by selecting unqualified SCs for the relevant sub-works. In the traditional way of SC selections, construction companies generally choose familiar SCs that had already done business with them. The benefits and problems of this kind of selection practices have been highlighted by several researchers. Tserng and Lin [17] pointed out the benefits of this kind of SC selection practices as flexibility, stability, mutual trust, decrease of transaction and search costs. On the other hand, difficulties in cost control and adoption of new technologies, and inefficiencies in SC selection and negotiation processes were some examples of the problems stated in their study. Additionally, they stated that lack of objective decision-making and reliable standards in sub-contracting selection and planning processes result in shortcomings during initial planning to predict overall performance and risk levels in carrying out a project. A simplified SC selection during the bidding process is illustrated in Fig. 2. The lowest bid price is usually the key determinant factor for selecting SCs in traditional approaches [17–19]. However, depending on the lowest bid price alone in the selection process, especially for complex construction
projects in which a more detailed evaluation methodology is usually needed may result in serious money losses for construction companies in the long run. It is relatively easy for the SCs to enter into the CI but many of them do not have the necessary expertise to complete the work satisfactorily [7,20]. Thus, inappropriate SCs that do not have the required expertise to carry out the work satisfactorily can be awarded the contract through this kind of selection practices. Selecting SCs without a systematic approach would generally cause problems in quality of work, delay in project duration and create additional costs in construction projects. Hence, this traditional approach to SC selection may not usually meet the needs of construction projects. Within this process, construction companies should therefore consider not only the bid price of the SCs but also several criteria such as past business experience, financial stability and quality of products. This method of assessment can eliminate insufficient financed, inexperienced and incompetent SCs, reduce risks and contribute significantly to the overall success of the project. Insufficient time for execution, complicated procedures or poor information channels may be the reasons of problems in the selection of SCs [21]. SC evaluation has been recognized as a particularly complex task due to its ambiguity and difficult formalisation [17,21,22]. It is usually based on intuition and past experience and carried out by the GC management [19,22]. There have been no generalized sets of rules for the evaluation process. However, when considered the limited time period of bids and the large number of SCs, it can be a difficult and complex task for construction contractors. The important factor in SC evaluation is that companies should reduce expert's subjectivity and it should be based on a combined assessment of various criteria. As a result, companies should implement a systematic evaluation process in the selection of the right SCs for the right job. 4. Previous studies
Fig. 2. Simplified sub-contractor selection during the bidding process.
Many selection methods for contractors and SCs have been proposed in the literature. In this part, contractor selection methodologies proposed in the literature have also been given considering that these can be adapted to SC selection where possible. Methods have been proposed using approaches such as multicriteria utility theory models [23], evidential reasoning [24], decision criteria [25], fuzzy set theory [26] and linear programming [27]. Rahman and Kumaraswamy [28] showed the importance of relational, trust and joint-responsibility-related factors for selecting different parties. Edum-Fotwe et al. [29] proposed transformed financial ratio models for improved contractor evaluation. Palaneeswaran and Kumaraswamy [6] focused on developing a model for contractor prequalification and bid evaluation in design and build projects. Moreover, Jaselskis and Russel [30], Crowley and Hancher [31], Russel [32], Kumaraswamy [33] and Alsugair [34] have identified commonly used criteria for prequalification and bid evaluation and have proposed methodologies for contractor selection. Alarcon and Mourgues [35] proposed a contractor selection system that incorporates the contractor's performance prediction
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as one of the criteria for selection. They developed a conceptual model that helps to identify information needed for a comprehensive evaluation and used it for the proposed contractor selection system. Russell and Skibniewski [36] developed QUALIFIER-1, a computer program to aid decision makers in prequalification. Then, Russell et al. [37] developed QUALIFIER-2 by adding some extra functions to QUALIFIER-1. Holt et al. [38–43] provided example applications of multiattribute analysis for evaluating construction bidders. Furthermore, Holt [44] reviewed and analyzed the use of different contractor selection methodologies and discussed the advantages and disadvantages of these methods. Kumaraswamy and Matthews [7] showed how partnering principles can be profitably applied to the SC selection process. Maturana et al. [1] developed an on-site evaluation method based on lean principles and partnering practices. The method supports SC selection based on their previous performance and allows GCs to help SCs improve their performance by providing them with periodic feedback. Albino and Garavelli [22] proposed a neural network application to support management in SC rating. They investigated the neural network implementation and the related managerial and technical innovations by an application case related to an assembly operation in a construction site. Tserng and Lin [17] developed an integrated XML (eXtensible Markup Language) of Accelerated Sub-contracting and Procuring (ASAP) model. They developed a web-based decision support system for GCs in order to decide an appropriate trade-off between risk and profit for different combinations of SCs. Luu and Sher [19] developed a case-based reasoning procurement advisory system for SC tender selection. In this system, SC selection cases are represented by a set of attributes elicited from experienced construction estimators. Shiau et al. [21] developed an SC selection management aid system, including basic database, budget management module and SC selection module. They acquired the evaluation criteria and calculated their weights by conducting surveys and using AHP (Analytical Hierarchy Process) and integrated them into the system. Ko et al. [45] developed a model called Sub-contractor Performance Evaluation Model (SPEM). In their study, an Evolutionary Fuzzy Neural Inference Model (EFNIM) is adapted as a learning and inference engine to execute the assessment process. Previous researches listed above had significantly improved the SC selection process in the CI. However, some of the proposed methods and approaches could be complex and difficult to apply in practice. The CI needs simple but effective methods in SC selection process due to the limited time intervals of the bidding periods. GCs have to prepare realistic and accurate bid proposals generally in a limited time period for the construction projects. Therefore, using complex, computational or mathematical models might not be effective in this process. Complex models and systems also require training of the personnel who will use such systems. Thus, a simple and user-friendly system that facilitates the SC selection process can be an effective method during the bidding process. WEBSES, the proposed system in this study, differs from the previous proposed methodologies and systems by its user-friendliness and faster eval-
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uation process. The main important issues of this system when compared to others are its practical usage, easiness to learn and simplicity. 5. Web-based sub-contractor evaluation system (WEBSES) In this part, the proposed SC evaluation system called WEBSES has been presented. The main objective of developing WEBSES is to facilitate the SC selection process in construction projects. In addition, it is aimed to minimize the problems that may occur in traditional selection processes as described earlier. The system is designed as a web-based system to perform the evaluation process more effectively. As mentioned earlier, the use of web-based technology provides great advantages in performing business activities. Skibniewski and Abduh [46] categorized the advantages of web technologies as; the support of relevant information services, communication between project participants, and engineering and management computing. Moreover, web applications have many benefits over desktop applications. They can reach a larger audience, and they are easier to install and develop. WEBSES can help the construction contractors to select the most appropriate SC that is highly critical during the bidding process. It allows GCs to evaluate the SCs in a systematic manner. The evaluation process is based on a combined criterion including cost, quality, time and adequacy as the main criteria. It is developed as a general system for all GCs and constructed under the Internet-based environment. The primary aim in the development phase of this system was to design it as a user-friendly system. Therefore, the system is designed such that every user can use it without having any training. One of the most important issues in the survey of this study (presented in the succeeding section) was the time limitation in preparing a bid proposal. In order to facilitate this process and create a simple but effective selection method, WEBSES is designed as a simple and user-friendly system. ASP (Active Server Pages) is adopted as the programming language for WEBSES. MySQL, one of the most popular Open Source Databases, is used in this system. It is a database management system that can handle large volume of data, and provide fast search and short processing time. A relatively new technique known as ‘AJAX’ (Asynchronous JavaScript And XML) is used to create a faster and more interactive web application. AJAX uses asynchronous data transfer between the browser and the web server that allows web pages to request small bits of information from the server instead of whole pages. Thus, it makes the web application faster and more user-friendly. AJAX is based on JavaScript, XML (eXtensible Markup Language), HTML (Hyper Text Markup Language) and CSS (Cascading Style Sheets) open standards. HTML has been successfully used since 1990 as a language used to create documents on the World Wide Web. However, it has major limitations such as extensibility, structure, and validation [12]. XML, designed by the W3C (World Wide Web Consortium), overcame these limitations by providing a more flexible and adaptable information identification [47]. CSS is a language used to specify the layout or formatting properties of HTML elements. For this
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Fig. 3. An example of an SC search result.
system, XHTML (eXtensible Hyper Text Markup Language) 1.1 validation is done. Thus, all browsers would likely to display the web pages in the same format. XHTML is a rewrite of the HTML as an XML application. Additionally, the XML files used in WEBSES are compatible with RSS (Really Simple Syndication), which is an XML-based format for content distribution. By adopting XHTML 1.1 and RSS to this system, the users are allowed to access information from WEBSES through different browser technologies such as mobile phones and Personal Digital Assistants (PDA). Furthermore, users can transfer information from this system to Microsoft Word in the same format. Every company user can access to this system by opening the web browser and using a password authorized by the GC. This application provides speedy access to the relevant information about the SCs. However, only the administrator has the permission for making necessary updates and changes in the system. The reason for giving the responsibility to the administrator is to provide a systematic updating progress and prevent the misuse of the users. There are three different authorization levels in this system. Users in level 1 can only search SCs from the database and take necessary information. Users in level 2 can add and evaluate SCs additionally to user level 1. Level 3 is the administrator level. The sub-options of the administration option consist of the following: user preferences, evaluation categories, subcontractors, sub-contractor information, evaluation criteria and work areas. GCs can evaluate SCs according to the evaluation criteria in the relevant options of the system. When adding new criteria by the administrator into the system, they can be assigned to one of the main criteria. Adding a criterion will cause a change in the weighting of the other criteria. However, this change is under the control of the administrator. In such conditions, the evaluation of the previously rated SCs will not change. The system consists of four options in the main menu including SC search, SC evaluation, user option and administrator option. The SC search option provides user's immediate access to the relevant SCs. The users can search SCs by the specialized areas of sub-works including site, concrete, materials, plastering, reinforcement, etc. Additionally, alternative search criteria in this system are the evaluation score and author name list. SCs can be listed according
to their overall, cost, quality, time and adequacy scores through the evaluation score option. Also the searching process can be done through ‘added by’ option in which author names who evaluated the relevant SCs in the past are listed. An example of an SC search result according to the same sub-group is shown in Fig. 3. Users can also rank SCs according to their evaluation scores on this web page. In the relevant SCs page, all necessary information including firm name, sub-work area, contacts and completed projects of the company could be obtained. 5.1. Identifying the criteria The main and sub-criteria for evaluating SCs in this system are identified according to a study conducted by the authors of this paper. The study is carried out in a mid-sized construction company based in New York (USA) during the period from 2001 to 2003. The company is a GC having a yearly business volume of approximately $200 million and focuses mainly on commercial projects in Tri-state area. The main objectives of the study were to investigate the problems encountered during SC selection and identify the criteria for selecting SCs in the bidding process. The study was carried out in the estimating and bidding department of the company. A chief estimator and two estimators participated in this study. During the period of the study, the SC selection process, problems in SC selection and the criteria for SC selection were investigated at each bid proposal preparation step of construction projects. For this purpose, face-to-face interviews were carried out with the participants regularly. The company generally sub-contracts a large volume of its work to the SCs. The estimating department of the company used a database in SC selection for the relevant sub-works. The database had a list of approximately 4000 SC firms however; it included only general information such as name, contact information and business areas of the SC firms. Past business records were not available in this database. A common problem caused by this lack of information was the re-selection of inadequate SCs that performed relatively unsuccessful works in the previous projects of the GC. It was observed that experienced estimators leaving the company with their knowledge gained in the past caused shortcomings in the selection of the right SCs.
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Fig. 4. Evaluation criteria for sub-contractor selection.
Fig. 5. An example of a sub-contractor evaluation result in WEBSES.
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Fig. 6. Quality evaluation option.
Since inexperienced estimators or new employees hired in the estimating department generally had not enough knowledge about all of the SCs listed in the database, proposals were submitted again for new projects to the inadequate SCs and awarded the contract. Furthermore, as there were not a systematic evaluation process and thus inadequate SCs were not eliminated, the GC dealt with many SCs in almost every bid proposal preparation of the projects. Thus, the company spent a great amount of time in almost every new project for the SC selection process. During the period of the study, several problems had arisen between the GC and the SCs. At the end of the study, these problems were categorized in four main headings as cost, quality, time and adequacy which are decided to be chosen as the main criteria in WEBSES. These four main headings had their sub-headings which are identified as the sub-criteria in this proposed system. The list of the sub-criteria under the main criteria is illustrated in Fig. 4.
The first step of the evaluation is the cost criteria option which is divided into the following sub-criteria: financial capacity, timely payment to laborers and completion of job within the budget. It should be noted that the GC can adjust the sub-criteria depending on the demand of each project. The critical point is that the selected sub-criteria should have a direct effect on performance. In addition, the selected evaluation criteria should
5.2. SC evaluation in WEBSES In the SC evaluation option, SCs can be evaluated according to the sets of evaluation criterion which are grouped under these headings: cost, quality, time and adequacy. Each of these main criteria is divided into sub-criteria. For instance, the cost criterion is divided into sub-criteria as financial capacity, timely payment to laborers and completion of job within the budget. In Fig. 5, an example of an SC evaluation result is illustrated. Also the last evaluation score and last three author evaluations regarding the SC can be seen on this web page. Additionally, the users can print or send these information as e-mail through the relevant options on this page. General information about the SCs are also posted on this web page.
Fig. 7. Evaluating and selecting sub-contractors using WEBSES.
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also based on the measurement culture of the GC. Each subcriterion will be scored on a 1 to 10 scale, 1 being unsatisfactory and 10 being satisfactory. Then, the SC's score will be calculated as a weighted sum of ratings over all sub-criteria, i.e., multiplication of each sub-criterion by their weights. In this study, the weights of main and sub-criteria are considered as equal. However, the GC can set different weights for them depending on the demand of each project. The sub-criteria of the cost option can be evaluated by the estimating department of the GC since these criteria are more relevant to this department. The estimating department can also evaluate the criteria in time and adequacy options whereas the construction department can evaluate those of quality, time and adequacy. The second step of the evaluation is the quality criteria option. An example of this option is shown in Fig. 6. Further steps include time and adequacy options. Similar to other options, adequacy scores are related with the past records of the SCs on the relevant criteria. For example the scores of adequacy of labor resources, one of the sub-criteria of adequacy, shows that whether the SC had enough labor resources in the previous projects or not. After completing the further steps the system will calculate the overall score of the SC. Then the GC can compare the result with other SC evaluations. Finally, the most appropriate SC can be selected based on the results of the evaluation scores. The answer of ‘who is the most appropriate one for the job?’ will be a critical judgement for the GC management. Depending only to overall score for the selection may not be the right way to choose the best SC. The GC may also consider the importance or weights of the main criteria. At this stage, the combination of the main criteria can be thought of as a chain, and as in any chain, it is the ‘weakest link’ that will cause the downfall. Therefore, the GC can consider the weakest link of the SCs that correspond to their lowest evaluation score of main criteria and make the selection according to it. For example, an SC may get a higher overall score from other SCs. However, if one of the evaluation scores of main criteria is far lower than the other SCs, the GC may eliminate this SC. The flowchart of evaluating and selecting SCs by using WEBSES is illustrated in Fig. 7. The system was implemented in the GC organization surveyed in this study. It was tested in the bid proposal preparation step of a construction project. The chief estimator and the two estimators used this system and evaluated the potential SCs for the project. After the evaluation process they determined and selected the SCs for the relevant sub-works. Benefits of the system were realised in the selection process. These benefits could be summarized as follows: • faster selection process • user-friendliness of the system • selection of the most appropriate SC with a systematic approach • reduction of subjectivity in evaluation • reduction in costs compared to traditional selection methods • competitive bid proposal The system can give the advantage of speed up the SC evaluation task during the bidding process. Although it is dif-
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ficult to calculate the exact time saving by using such a system, it is believed that it can significantly reduce the overall amount of time required for SC selection when compared to the traditional approaches. Having past business records and immediate access to relevant information of SCs, it can improve the selection process. 6. Conclusions SC selection in construction projects is crucial. Choosing the right SC for the right job influences the quality of work as well as the construction progress. Especially during the bidding process optimum selection of SCs is vital for an accurate and realistic bid proposal. As construction projects and sub-contract works become more complex, a combined assessment of various criteria should be considered by the GCs in order to select the most suitable one. Traditional selection of SCs such as choosing those with whom the GC had already done business can lead to inefficiencies in projects and poor project performance. The proposed system in this paper, WEBSES, can help to improve the selection process and obtain the best decision of selecting an SC. It can reduce the overall amount of time required for the selection process. Objective evaluation with various criteria can lead to the elimination of unqualified SCs during the bidding process. WEBSES is developed for the use by GCs. A fair and objective assessment is provided by this system. It eliminates the dependence on lowest bid price by considering a combined criterion. WEBSES can speed up the sub-contracting process and improve the decision quality. It can also reduce costs of the selection process. Therefore, problems that arise from traditional practices can be avoided. The overall benefit of selecting the most suitable SC can be the improvement of the GC's overall performance. If properly done, SC evaluation through WEBSES could be an effective way in the selection of the right SCs for the sub-contract works of the construction projects. References [1] S. Maturana, L. Alarcon, P. Gazmuri, M. Vrsalovi, Achieving collaboration in the construction supply chain: an on-site subcontractor evaluation method, Documento de Trabajo, Pontificia Universidad Catolica de Chile, 2005 No.177. [2] S.T. Ng, M. Skitmore, W.F. Chung, Ten basic factors to identify suitable subcontractors for construction projects, CIB TG 23 International Conference, Hong Kong, 2003. [3] A.A. Shash, Bidding practices of subcontractors in Colorado, ASCE Journal of Construction Engineering and Management 124 (3) (1998) 219–225. [4] D. Arditi, R. Chotibhongs, Issues in subcontracting practice, ASCE Journal of Construction Engineering and Management 131 (8) (2005) 866–876. [5] R.F. Cox, R.R.A. Issa, A. Frey, Proposed subcontractor-based employee motivational model, ASCE Journal of Construction Engineering and Management 132 (2) (2006) 152–163. [6] E. Palaneeswaran, M.M. Kumaraswamy, Contractor selection for design/ build projects, ASCE Journal of Construction Engineering and Management 126 (5) (2000) 331–339. [7] M.M. Kumaraswamy, J. Matthews, Improved subcontractor selection employing partnering principles, ASCE Journal of Management in Engineering 16 (3) (2000) 47–57.
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[8] S.T. Ng, W.Y. Wan, Appraisal of subcontractor performance — criteria and their importance, in: A.S. Kazi (Ed.), Proceedings of CIB2005— Advancing Facilities Management and Construction through Innovation, Finlandia Hall, Helsinki, Finland, 2005, pp. 305–314, Finland, III. [9] P. Nitithamyong, M.J. Skibniewski, Web-based construction project management systems: how to make them successful? Automation in Construction 13 (4) (2004) 491–506. [10] V. Peansupap, D.H.T. Walker, Factors enabling information and communication technology diffusion and actual implementation in construction organisations, Journal of Information Technology in Construction 10 (2005) 193–218. [11] P. Nitithamyong, M.J. Skibniewski, Success/failure factors and performance measures of web-based construction project management systems: professionals' viewpoint, ASCE Journal of Construction Engineering and Management 132 (1) (2006) 80–87. [12] Y. Zhu, R.R.A. Issa, R.F. Cox, Web-based construction document processing via malleable frame, ASCE Journal of Computing in Civil Engineering 15 (3) (2001) 157–169. [13] I. Dikmen, M.T. Birgonul, Neural network model to support international market entry decisions, ASCE Journal of Construction Engineering and Management 130 (1) (2004) 59–66. [14] C. Halaris, G. Bafoutsou, G. Papavassiliou, G. Mentzas, A system for virtual tendering and bidding, 8th Panhellinic Conference in Informatics, Cyprus, 2001. [15] G. Arslan, M. Tuncan, M.T. Birgonul, I. Dikmen, E-bidding proposal preparation system for construction projects, Building and Environment 41 (10) (2006) 1406–1413. [16] I. Dikmen, M.T. Birgonul, Strategic perspective of Turkish construction companies, ASCE Journal of Management in Engineering 19 (1) (2003) 33–40. [17] H.P. Tserng, P.H. Lin, An accelerated subcontracting and procuring model for construction projects, Automation in Construction 11 (1) (2002) 105–125. [18] E. Tam, STAT-USA market research reports, U.S. & Foreign Commercial Service and U.S. Department of State, 2003. [19] D.T. Luu, W. Sher, Construction tender subcontract selection using casebased reasoning, The Australian Journal of Construction Economics and Building, Australian Institute of Quantity Surveyors 6 (2) (2006) 31–43. [20] T. Hegazy, T. Ersahin, Simplified spreadsheet solutions I: subcontractor information system, ASCE Journal of Construction Engineering and Management 127 (6) (2001) 461–468. [21] Y.C. Shiau, T.P. Tsai, W.C. Wang, M.L. Huang, Use questionnaire and AHP techniques to develop subcontractor selection system, International Symposium on Automation and Robotics in Construction, 19th (ISARC) Proceedings, National Institute of Standards and Technology, Gaithersburg, Maryland, 2002, pp. 35–40. [22] V. Albino, A.C. Garavelli, A neural network application to subcontractor rating in construction firms, International Journal of Project Management 16 (1) (1998) 9–14. [23] Z. Hatush, M. Skitmore, Contractor selection using multicriteria utility theory: an additive model, Building and Environment 33 (2–3) (1998) 105–115. [24] M. Sonmez, G. Holt, J.B. Yang, G. Graham, Applying evidential reasoning to prequalifying construction contractors, ASCE Journal of Management in Engineering 18 (3) (2002) 111–119. [25] J.S. Russell, M.J. Skibniewski, Decision criteria in contractor prequalification, ASCE Journal of Management in Engineering 4 (2) (1988) 148–164. [26] D. Singh, R. Tiong, A fuzzy decision framework for contractor selection, ASCE Journal of Construction Engineering and Management 131 (1) (2005) 62–70.
[27] A. Elazouni, F. Metwally, D-SUB: decision support system for subcontracting construction works, ASCE Journal of Construction Engineering and Management 126 (3) (2000) 191–200. [28] M. Rahman, M.M. Kumaraswamy, Potential for implementing relational contracting and joint risk management, ASCE Journal of Management in Engineering 20 (4) (2004) 178–189. [29] F.E. Edum-Fotwe, A.D.F. Price, A. Thorpe, Transformed financial ratio models for improved contractor evaluation, Proc., 1st International Conference on Construction Project Management, Nanyang Technological University, Singapore, 1995, pp. 559–567. [30] E.J. Jaselskis, J.S. Russell, Risk analysis approach to selection of contractor evaluation method, ASCE Journal of Construction Engineering and Management 118 (4) (1992) 814–821. [31] L.G. Crowley, D.E. Hancher, Evaluation of competitive bids, ASCE Journal of Construction Engineering and Management 121 (2) (1995) 238–245. [32] J.S. Russell, Constructor prequalification-choosing the best contractor and avoiding constructor failure, ASCE Press, New York, 1996. [33] M.M. Kumaraswamy, Contractor evaluation and selection — a Hong Kong perspective, Building and Environment 31 (3) (1996) 273–282. [34] A.M. Alsugair, Framework for evaluating bids of construction contractors, ASCE Journal of Management in Engineering 15 (2) (1999) 72–78. [35] L.F. Alarcon, C. Mourgues, Performance modelling for contractor selection, ASCE Journal of Management in Engineering 18 (2) (2002) 52–60. [36] J.S. Russell, M.J. Skibniewski, QUALIFIER-1: contractor prequalification model, ASCE Journal of Computing in Civil Engineering 4 (1) (1990) 77–90. [37] J.S. Russell, M.J. Skibniewski, D.R. Cozier, QUALIFIER-2: knowledgebased system for contractor prequalification, ASCE Journal of Construction Engineering and Management 116 (1) (1990) 157–171. [38] G.D. Holt, P.O. Olomolaiye, F.C. Harris, A conceptual alternative to current tendering practice, Building Research and Information 21 (3) (1993) 167–172. [39] G.D. Holt, P.O. Olomolaiye, F.C. Harris, Factors influencing U.K. construction clients' choice of contractor, Building and Environment 29 (2) (1994) 241–248. [40] G.D. Holt, P.O. Olomolaiye, F.C. Harris, Applying multi-attribute analysis to contractor selection decisions, European Journal of Purchasing and Supply Management 1 (3) (1994) 139–148. [41] G.D. Holt, P.O. Olomolaiye, F.C. Harris, Incorporating project specific criteria and client utility into the evaluation of construction tenderers, Building Research and Information 22 (4) (1994) 214–221. [42] G.D. Holt, P.O. Olomolaiye, F.C. Harris, Evaluating pre-qualification criteria in contractor selection, Building and Environment 29 (4) (1994) 437–448. [43] G.D. Holt, P.O. Olomolaiye, F.C. Harris, Application of an alternative contractor selection model, Building Research and Information 23 (5) (1995) 255–264. [44] G.D. Holt, Which contractor selection methodology? International Journal of Project Management 16 (3) (1998) 153–164. [45] C.H. Ko, M.Y. Cheng, T.K. Wu, Evaluating sub-contractors performance using EFNIM, Automation in Construction 16 (4) (2007) 525–530. [46] M.J. Skibniewski, M. Abduh, Web-based project management for construction: search for utility assessment tools, Proceedings of INCITE 2000, Hong Kong Polytechnic University, Hong Kong, 2000, pp. 56–77. [47] Y. Zhu, R.R.A. Issa, Viewer controllable visualization for construction document processing, Automation in Construction 12 (3) (2003) 255–269.
Improving sub-contractor selection process in construction projects: Web-based sub-contractor evaluation system (WEBSES) Gokhan Arslan a,⁎, Serkan Kivrak a , M. Talat Birgonul b , Irem Dikmen b a
b
Anadolu University, Civil Engineering Department, 26555 Eskisehir, Turkey Middle East Technical University, Civil Engineering Department, 06531 Ankara, Turkey Accepted 14 August 2007
Abstract One of the most important phases in the construction industry (CI) is the bidding process. During the bidding process, selecting the most appropriate sub-contractors (SCs) for the relevant sub-works is highly critical for the overall project performance. In order to select the most appropriate SCs for the project and prepare the most realistic and accurate bid proposal, general contractors (GCs) have to know all financial, technical and general information about these SCs. Within this context, GCs should consider several factors in the selection process. These factors may include the quality of production, efficiency, employment of qualified members, reputation of the company, accessibility to the company, completion of the work on time etc. This paper proposes a web-based sub-contractor evaluation system called WEBSES by which the SCs can be evaluated based on a combined criterion. It enables GCs to select the most appropriate SCs for their relevant sub-works, speed up the selection process and gain time and cost savings during the bidding process. © 2007 Elsevier B.V. All rights reserved. Keywords: Sub-contractor; Construction industry; Information technology (IT); Evaluation
1. Introduction Sub-contracting has extensively been used in the CI. It allows GCs to employ a minimum workforce in construction projects and promotes specialization [1,2]. Many GCs only act as construction management agents in construction projects and sub-contract a large volume of their work to SCs [3]. SCs play an important role in the success of construction projects [4,5]. The success level of these projects may depend on the philosophy of selecting “the right person for the right job” [6]. Clearly, the correct choice of SCs increases the overall success of a construction project. However, the importance of SC selection is mostly underestimated and neglected in construction [7,8]. SC evaluation is a vital part of the project management cycle. As construction projects become more complex, the need for
⁎ Corresponding author. Tel.: +90 222 321 35 50; fax: +90 222 323 95 01. E-mail addresses: [email protected] (G. Arslan), [email protected] (S. Kivrak), [email protected] (M.T. Birgonul), [email protected] (I. Dikmen). 0926-5805/$ - see front matter © 2007 Elsevier B.V. All rights reserved. doi:10.1016/j.autcon.2007.08.004
evaluating SC performance becomes more crucial. Although there are no generalized sets of rules in evaluating SCs, several factors should be considered by the GC in the selection process. These factors may include the quality of production, efficiency, employment of qualified members, reputation of the company, accessibility to the company, completion of the work on time, etc. The use of information technology (IT) applications in the CI has been recognized as highly essential for improving business performance [9,10]. IT tools enable companies to speed up the business activities. Especially, Internet-based technology has been recognized as the most important tool to facilitate information transfer effectively and a collaborative working environment in construction projects [11]. A considerable amount of time and cost saving can be achieved by the use of Internet technologies. A construction company has generally several projects that are located in different geographical areas. Information exchange can be performed effectively between the members of these projects through the use of web-based applications. Thus, problems caused by geographic fragmentation can significantly be reduced [12]. When considered the advantages, the use of web-based technology can be an effective
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way in the SC evaluation process. This paper presents a webbased sub-contractor evaluation system called WEBSES by which the SCs can be evaluated based on a combined criterion. GCs can select the most appropriate SCs for their relevant subworks, speed up the selection process and gain the advantage of saving time and cost during the bidding process through this system. 2. Bidding process in the construction industry Bidding for construction projects is a critical decision for construction companies. It is especially crucial for international construction projects by which the companies aim to position themselves in the international construction market [13]. The bidding process is also a critical task in the construction industry. The amount of profit level is critically determined at this stage. Since the major objective of the construction companies is to expand business volume by successful bidding on various projects, preparing realistic and accurate bid proposals is the most significant component for the expansion. The bidding process in the CI is characterized by the involvement of many different parties including the client, architectural and engineering firms, GCs, specialized contractors, material suppliers, manufactur ers, etc [14]. Preparing tender documents, evaluating bids, and
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awarding the contract to the winner of the bid are among the major duties of the client. The GCs also follow the same sequential procedure for the selection of their SCs [15]. Construction company's bidding strategies change according to bidding system, client, country and bid evaluation criteria [16]. The methods of preparing bid proposals for construction projects also vary according to the structure and characteristics of the project. The bidding process requires a great deal of time and effort especially for complex projects. Therefore, a systematic procedure should be followed to prepare bid proposals for such projects. In Fig. 1, the necessary phases that should be followed for bid proposal preparation are illustrated. It should be noted that these phases are summarized according to the traditional approach of the bidding process, that is, without using the latest technologies such as e-bidding. It should also be considered that any omitted item in these phases would cause delays or mistakes in the bidding process. 3. Sub-contractor selection in the bidding process In the CI, biddings usually occur between GCs and SCs. GCs rely mostly on the bid prices submitted by the SCs to estimate the final bid sum for the projects. Thus, SCs play an important role in the bidding process. During the bidding process, selecting the
Fig. 1. Phases during a typical bidding process.
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most appropriate SCs for the sub-works is highly critical. Therefore, GCs must be extremely careful while selecting the most appropriate SC for a certain part of the work or the entire project [15]. They have to be fair and objective in their relations with the SCs. Poor selection of SCs may lead to the elimination of qualified SCs from business or result in a lowering of their standards, thus, producing cheap and poor quality work [3]. Also the GCs may loose time and money by selecting unqualified SCs for the relevant sub-works. In the traditional way of SC selections, construction companies generally choose familiar SCs that had already done business with them. The benefits and problems of this kind of selection practices have been highlighted by several researchers. Tserng and Lin [17] pointed out the benefits of this kind of SC selection practices as flexibility, stability, mutual trust, decrease of transaction and search costs. On the other hand, difficulties in cost control and adoption of new technologies, and inefficiencies in SC selection and negotiation processes were some examples of the problems stated in their study. Additionally, they stated that lack of objective decision-making and reliable standards in sub-contracting selection and planning processes result in shortcomings during initial planning to predict overall performance and risk levels in carrying out a project. A simplified SC selection during the bidding process is illustrated in Fig. 2. The lowest bid price is usually the key determinant factor for selecting SCs in traditional approaches [17–19]. However, depending on the lowest bid price alone in the selection process, especially for complex construction
projects in which a more detailed evaluation methodology is usually needed may result in serious money losses for construction companies in the long run. It is relatively easy for the SCs to enter into the CI but many of them do not have the necessary expertise to complete the work satisfactorily [7,20]. Thus, inappropriate SCs that do not have the required expertise to carry out the work satisfactorily can be awarded the contract through this kind of selection practices. Selecting SCs without a systematic approach would generally cause problems in quality of work, delay in project duration and create additional costs in construction projects. Hence, this traditional approach to SC selection may not usually meet the needs of construction projects. Within this process, construction companies should therefore consider not only the bid price of the SCs but also several criteria such as past business experience, financial stability and quality of products. This method of assessment can eliminate insufficient financed, inexperienced and incompetent SCs, reduce risks and contribute significantly to the overall success of the project. Insufficient time for execution, complicated procedures or poor information channels may be the reasons of problems in the selection of SCs [21]. SC evaluation has been recognized as a particularly complex task due to its ambiguity and difficult formalisation [17,21,22]. It is usually based on intuition and past experience and carried out by the GC management [19,22]. There have been no generalized sets of rules for the evaluation process. However, when considered the limited time period of bids and the large number of SCs, it can be a difficult and complex task for construction contractors. The important factor in SC evaluation is that companies should reduce expert's subjectivity and it should be based on a combined assessment of various criteria. As a result, companies should implement a systematic evaluation process in the selection of the right SCs for the right job. 4. Previous studies
Fig. 2. Simplified sub-contractor selection during the bidding process.
Many selection methods for contractors and SCs have been proposed in the literature. In this part, contractor selection methodologies proposed in the literature have also been given considering that these can be adapted to SC selection where possible. Methods have been proposed using approaches such as multicriteria utility theory models [23], evidential reasoning [24], decision criteria [25], fuzzy set theory [26] and linear programming [27]. Rahman and Kumaraswamy [28] showed the importance of relational, trust and joint-responsibility-related factors for selecting different parties. Edum-Fotwe et al. [29] proposed transformed financial ratio models for improved contractor evaluation. Palaneeswaran and Kumaraswamy [6] focused on developing a model for contractor prequalification and bid evaluation in design and build projects. Moreover, Jaselskis and Russel [30], Crowley and Hancher [31], Russel [32], Kumaraswamy [33] and Alsugair [34] have identified commonly used criteria for prequalification and bid evaluation and have proposed methodologies for contractor selection. Alarcon and Mourgues [35] proposed a contractor selection system that incorporates the contractor's performance prediction
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as one of the criteria for selection. They developed a conceptual model that helps to identify information needed for a comprehensive evaluation and used it for the proposed contractor selection system. Russell and Skibniewski [36] developed QUALIFIER-1, a computer program to aid decision makers in prequalification. Then, Russell et al. [37] developed QUALIFIER-2 by adding some extra functions to QUALIFIER-1. Holt et al. [38–43] provided example applications of multiattribute analysis for evaluating construction bidders. Furthermore, Holt [44] reviewed and analyzed the use of different contractor selection methodologies and discussed the advantages and disadvantages of these methods. Kumaraswamy and Matthews [7] showed how partnering principles can be profitably applied to the SC selection process. Maturana et al. [1] developed an on-site evaluation method based on lean principles and partnering practices. The method supports SC selection based on their previous performance and allows GCs to help SCs improve their performance by providing them with periodic feedback. Albino and Garavelli [22] proposed a neural network application to support management in SC rating. They investigated the neural network implementation and the related managerial and technical innovations by an application case related to an assembly operation in a construction site. Tserng and Lin [17] developed an integrated XML (eXtensible Markup Language) of Accelerated Sub-contracting and Procuring (ASAP) model. They developed a web-based decision support system for GCs in order to decide an appropriate trade-off between risk and profit for different combinations of SCs. Luu and Sher [19] developed a case-based reasoning procurement advisory system for SC tender selection. In this system, SC selection cases are represented by a set of attributes elicited from experienced construction estimators. Shiau et al. [21] developed an SC selection management aid system, including basic database, budget management module and SC selection module. They acquired the evaluation criteria and calculated their weights by conducting surveys and using AHP (Analytical Hierarchy Process) and integrated them into the system. Ko et al. [45] developed a model called Sub-contractor Performance Evaluation Model (SPEM). In their study, an Evolutionary Fuzzy Neural Inference Model (EFNIM) is adapted as a learning and inference engine to execute the assessment process. Previous researches listed above had significantly improved the SC selection process in the CI. However, some of the proposed methods and approaches could be complex and difficult to apply in practice. The CI needs simple but effective methods in SC selection process due to the limited time intervals of the bidding periods. GCs have to prepare realistic and accurate bid proposals generally in a limited time period for the construction projects. Therefore, using complex, computational or mathematical models might not be effective in this process. Complex models and systems also require training of the personnel who will use such systems. Thus, a simple and user-friendly system that facilitates the SC selection process can be an effective method during the bidding process. WEBSES, the proposed system in this study, differs from the previous proposed methodologies and systems by its user-friendliness and faster eval-
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uation process. The main important issues of this system when compared to others are its practical usage, easiness to learn and simplicity. 5. Web-based sub-contractor evaluation system (WEBSES) In this part, the proposed SC evaluation system called WEBSES has been presented. The main objective of developing WEBSES is to facilitate the SC selection process in construction projects. In addition, it is aimed to minimize the problems that may occur in traditional selection processes as described earlier. The system is designed as a web-based system to perform the evaluation process more effectively. As mentioned earlier, the use of web-based technology provides great advantages in performing business activities. Skibniewski and Abduh [46] categorized the advantages of web technologies as; the support of relevant information services, communication between project participants, and engineering and management computing. Moreover, web applications have many benefits over desktop applications. They can reach a larger audience, and they are easier to install and develop. WEBSES can help the construction contractors to select the most appropriate SC that is highly critical during the bidding process. It allows GCs to evaluate the SCs in a systematic manner. The evaluation process is based on a combined criterion including cost, quality, time and adequacy as the main criteria. It is developed as a general system for all GCs and constructed under the Internet-based environment. The primary aim in the development phase of this system was to design it as a user-friendly system. Therefore, the system is designed such that every user can use it without having any training. One of the most important issues in the survey of this study (presented in the succeeding section) was the time limitation in preparing a bid proposal. In order to facilitate this process and create a simple but effective selection method, WEBSES is designed as a simple and user-friendly system. ASP (Active Server Pages) is adopted as the programming language for WEBSES. MySQL, one of the most popular Open Source Databases, is used in this system. It is a database management system that can handle large volume of data, and provide fast search and short processing time. A relatively new technique known as ‘AJAX’ (Asynchronous JavaScript And XML) is used to create a faster and more interactive web application. AJAX uses asynchronous data transfer between the browser and the web server that allows web pages to request small bits of information from the server instead of whole pages. Thus, it makes the web application faster and more user-friendly. AJAX is based on JavaScript, XML (eXtensible Markup Language), HTML (Hyper Text Markup Language) and CSS (Cascading Style Sheets) open standards. HTML has been successfully used since 1990 as a language used to create documents on the World Wide Web. However, it has major limitations such as extensibility, structure, and validation [12]. XML, designed by the W3C (World Wide Web Consortium), overcame these limitations by providing a more flexible and adaptable information identification [47]. CSS is a language used to specify the layout or formatting properties of HTML elements. For this
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Fig. 3. An example of an SC search result.
system, XHTML (eXtensible Hyper Text Markup Language) 1.1 validation is done. Thus, all browsers would likely to display the web pages in the same format. XHTML is a rewrite of the HTML as an XML application. Additionally, the XML files used in WEBSES are compatible with RSS (Really Simple Syndication), which is an XML-based format for content distribution. By adopting XHTML 1.1 and RSS to this system, the users are allowed to access information from WEBSES through different browser technologies such as mobile phones and Personal Digital Assistants (PDA). Furthermore, users can transfer information from this system to Microsoft Word in the same format. Every company user can access to this system by opening the web browser and using a password authorized by the GC. This application provides speedy access to the relevant information about the SCs. However, only the administrator has the permission for making necessary updates and changes in the system. The reason for giving the responsibility to the administrator is to provide a systematic updating progress and prevent the misuse of the users. There are three different authorization levels in this system. Users in level 1 can only search SCs from the database and take necessary information. Users in level 2 can add and evaluate SCs additionally to user level 1. Level 3 is the administrator level. The sub-options of the administration option consist of the following: user preferences, evaluation categories, subcontractors, sub-contractor information, evaluation criteria and work areas. GCs can evaluate SCs according to the evaluation criteria in the relevant options of the system. When adding new criteria by the administrator into the system, they can be assigned to one of the main criteria. Adding a criterion will cause a change in the weighting of the other criteria. However, this change is under the control of the administrator. In such conditions, the evaluation of the previously rated SCs will not change. The system consists of four options in the main menu including SC search, SC evaluation, user option and administrator option. The SC search option provides user's immediate access to the relevant SCs. The users can search SCs by the specialized areas of sub-works including site, concrete, materials, plastering, reinforcement, etc. Additionally, alternative search criteria in this system are the evaluation score and author name list. SCs can be listed according
to their overall, cost, quality, time and adequacy scores through the evaluation score option. Also the searching process can be done through ‘added by’ option in which author names who evaluated the relevant SCs in the past are listed. An example of an SC search result according to the same sub-group is shown in Fig. 3. Users can also rank SCs according to their evaluation scores on this web page. In the relevant SCs page, all necessary information including firm name, sub-work area, contacts and completed projects of the company could be obtained. 5.1. Identifying the criteria The main and sub-criteria for evaluating SCs in this system are identified according to a study conducted by the authors of this paper. The study is carried out in a mid-sized construction company based in New York (USA) during the period from 2001 to 2003. The company is a GC having a yearly business volume of approximately $200 million and focuses mainly on commercial projects in Tri-state area. The main objectives of the study were to investigate the problems encountered during SC selection and identify the criteria for selecting SCs in the bidding process. The study was carried out in the estimating and bidding department of the company. A chief estimator and two estimators participated in this study. During the period of the study, the SC selection process, problems in SC selection and the criteria for SC selection were investigated at each bid proposal preparation step of construction projects. For this purpose, face-to-face interviews were carried out with the participants regularly. The company generally sub-contracts a large volume of its work to the SCs. The estimating department of the company used a database in SC selection for the relevant sub-works. The database had a list of approximately 4000 SC firms however; it included only general information such as name, contact information and business areas of the SC firms. Past business records were not available in this database. A common problem caused by this lack of information was the re-selection of inadequate SCs that performed relatively unsuccessful works in the previous projects of the GC. It was observed that experienced estimators leaving the company with their knowledge gained in the past caused shortcomings in the selection of the right SCs.
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Fig. 4. Evaluation criteria for sub-contractor selection.
Fig. 5. An example of a sub-contractor evaluation result in WEBSES.
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Fig. 6. Quality evaluation option.
Since inexperienced estimators or new employees hired in the estimating department generally had not enough knowledge about all of the SCs listed in the database, proposals were submitted again for new projects to the inadequate SCs and awarded the contract. Furthermore, as there were not a systematic evaluation process and thus inadequate SCs were not eliminated, the GC dealt with many SCs in almost every bid proposal preparation of the projects. Thus, the company spent a great amount of time in almost every new project for the SC selection process. During the period of the study, several problems had arisen between the GC and the SCs. At the end of the study, these problems were categorized in four main headings as cost, quality, time and adequacy which are decided to be chosen as the main criteria in WEBSES. These four main headings had their sub-headings which are identified as the sub-criteria in this proposed system. The list of the sub-criteria under the main criteria is illustrated in Fig. 4.
The first step of the evaluation is the cost criteria option which is divided into the following sub-criteria: financial capacity, timely payment to laborers and completion of job within the budget. It should be noted that the GC can adjust the sub-criteria depending on the demand of each project. The critical point is that the selected sub-criteria should have a direct effect on performance. In addition, the selected evaluation criteria should
5.2. SC evaluation in WEBSES In the SC evaluation option, SCs can be evaluated according to the sets of evaluation criterion which are grouped under these headings: cost, quality, time and adequacy. Each of these main criteria is divided into sub-criteria. For instance, the cost criterion is divided into sub-criteria as financial capacity, timely payment to laborers and completion of job within the budget. In Fig. 5, an example of an SC evaluation result is illustrated. Also the last evaluation score and last three author evaluations regarding the SC can be seen on this web page. Additionally, the users can print or send these information as e-mail through the relevant options on this page. General information about the SCs are also posted on this web page.
Fig. 7. Evaluating and selecting sub-contractors using WEBSES.
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also based on the measurement culture of the GC. Each subcriterion will be scored on a 1 to 10 scale, 1 being unsatisfactory and 10 being satisfactory. Then, the SC's score will be calculated as a weighted sum of ratings over all sub-criteria, i.e., multiplication of each sub-criterion by their weights. In this study, the weights of main and sub-criteria are considered as equal. However, the GC can set different weights for them depending on the demand of each project. The sub-criteria of the cost option can be evaluated by the estimating department of the GC since these criteria are more relevant to this department. The estimating department can also evaluate the criteria in time and adequacy options whereas the construction department can evaluate those of quality, time and adequacy. The second step of the evaluation is the quality criteria option. An example of this option is shown in Fig. 6. Further steps include time and adequacy options. Similar to other options, adequacy scores are related with the past records of the SCs on the relevant criteria. For example the scores of adequacy of labor resources, one of the sub-criteria of adequacy, shows that whether the SC had enough labor resources in the previous projects or not. After completing the further steps the system will calculate the overall score of the SC. Then the GC can compare the result with other SC evaluations. Finally, the most appropriate SC can be selected based on the results of the evaluation scores. The answer of ‘who is the most appropriate one for the job?’ will be a critical judgement for the GC management. Depending only to overall score for the selection may not be the right way to choose the best SC. The GC may also consider the importance or weights of the main criteria. At this stage, the combination of the main criteria can be thought of as a chain, and as in any chain, it is the ‘weakest link’ that will cause the downfall. Therefore, the GC can consider the weakest link of the SCs that correspond to their lowest evaluation score of main criteria and make the selection according to it. For example, an SC may get a higher overall score from other SCs. However, if one of the evaluation scores of main criteria is far lower than the other SCs, the GC may eliminate this SC. The flowchart of evaluating and selecting SCs by using WEBSES is illustrated in Fig. 7. The system was implemented in the GC organization surveyed in this study. It was tested in the bid proposal preparation step of a construction project. The chief estimator and the two estimators used this system and evaluated the potential SCs for the project. After the evaluation process they determined and selected the SCs for the relevant sub-works. Benefits of the system were realised in the selection process. These benefits could be summarized as follows: • faster selection process • user-friendliness of the system • selection of the most appropriate SC with a systematic approach • reduction of subjectivity in evaluation • reduction in costs compared to traditional selection methods • competitive bid proposal The system can give the advantage of speed up the SC evaluation task during the bidding process. Although it is dif-
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ficult to calculate the exact time saving by using such a system, it is believed that it can significantly reduce the overall amount of time required for SC selection when compared to the traditional approaches. Having past business records and immediate access to relevant information of SCs, it can improve the selection process. 6. Conclusions SC selection in construction projects is crucial. Choosing the right SC for the right job influences the quality of work as well as the construction progress. Especially during the bidding process optimum selection of SCs is vital for an accurate and realistic bid proposal. As construction projects and sub-contract works become more complex, a combined assessment of various criteria should be considered by the GCs in order to select the most suitable one. Traditional selection of SCs such as choosing those with whom the GC had already done business can lead to inefficiencies in projects and poor project performance. The proposed system in this paper, WEBSES, can help to improve the selection process and obtain the best decision of selecting an SC. It can reduce the overall amount of time required for the selection process. Objective evaluation with various criteria can lead to the elimination of unqualified SCs during the bidding process. WEBSES is developed for the use by GCs. A fair and objective assessment is provided by this system. It eliminates the dependence on lowest bid price by considering a combined criterion. WEBSES can speed up the sub-contracting process and improve the decision quality. It can also reduce costs of the selection process. Therefore, problems that arise from traditional practices can be avoided. The overall benefit of selecting the most suitable SC can be the improvement of the GC's overall performance. If properly done, SC evaluation through WEBSES could be an effective way in the selection of the right SCs for the sub-contract works of the construction projects. References [1] S. Maturana, L. Alarcon, P. Gazmuri, M. Vrsalovi, Achieving collaboration in the construction supply chain: an on-site subcontractor evaluation method, Documento de Trabajo, Pontificia Universidad Catolica de Chile, 2005 No.177. [2] S.T. Ng, M. Skitmore, W.F. Chung, Ten basic factors to identify suitable subcontractors for construction projects, CIB TG 23 International Conference, Hong Kong, 2003. [3] A.A. Shash, Bidding practices of subcontractors in Colorado, ASCE Journal of Construction Engineering and Management 124 (3) (1998) 219–225. [4] D. Arditi, R. Chotibhongs, Issues in subcontracting practice, ASCE Journal of Construction Engineering and Management 131 (8) (2005) 866–876. [5] R.F. Cox, R.R.A. Issa, A. Frey, Proposed subcontractor-based employee motivational model, ASCE Journal of Construction Engineering and Management 132 (2) (2006) 152–163. [6] E. Palaneeswaran, M.M. Kumaraswamy, Contractor selection for design/ build projects, ASCE Journal of Construction Engineering and Management 126 (5) (2000) 331–339. [7] M.M. Kumaraswamy, J. Matthews, Improved subcontractor selection employing partnering principles, ASCE Journal of Management in Engineering 16 (3) (2000) 47–57.
488
G. Arslan et al. / Automation in Construction 17 (2008) 480–488
[8] S.T. Ng, W.Y. Wan, Appraisal of subcontractor performance — criteria and their importance, in: A.S. Kazi (Ed.), Proceedings of CIB2005— Advancing Facilities Management and Construction through Innovation, Finlandia Hall, Helsinki, Finland, 2005, pp. 305–314, Finland, III. [9] P. Nitithamyong, M.J. Skibniewski, Web-based construction project management systems: how to make them successful? Automation in Construction 13 (4) (2004) 491–506. [10] V. Peansupap, D.H.T. Walker, Factors enabling information and communication technology diffusion and actual implementation in construction organisations, Journal of Information Technology in Construction 10 (2005) 193–218. [11] P. Nitithamyong, M.J. Skibniewski, Success/failure factors and performance measures of web-based construction project management systems: professionals' viewpoint, ASCE Journal of Construction Engineering and Management 132 (1) (2006) 80–87. [12] Y. Zhu, R.R.A. Issa, R.F. Cox, Web-based construction document processing via malleable frame, ASCE Journal of Computing in Civil Engineering 15 (3) (2001) 157–169. [13] I. Dikmen, M.T. Birgonul, Neural network model to support international market entry decisions, ASCE Journal of Construction Engineering and Management 130 (1) (2004) 59–66. [14] C. Halaris, G. Bafoutsou, G. Papavassiliou, G. Mentzas, A system for virtual tendering and bidding, 8th Panhellinic Conference in Informatics, Cyprus, 2001. [15] G. Arslan, M. Tuncan, M.T. Birgonul, I. Dikmen, E-bidding proposal preparation system for construction projects, Building and Environment 41 (10) (2006) 1406–1413. [16] I. Dikmen, M.T. Birgonul, Strategic perspective of Turkish construction companies, ASCE Journal of Management in Engineering 19 (1) (2003) 33–40. [17] H.P. Tserng, P.H. Lin, An accelerated subcontracting and procuring model for construction projects, Automation in Construction 11 (1) (2002) 105–125. [18] E. Tam, STAT-USA market research reports, U.S. & Foreign Commercial Service and U.S. Department of State, 2003. [19] D.T. Luu, W. Sher, Construction tender subcontract selection using casebased reasoning, The Australian Journal of Construction Economics and Building, Australian Institute of Quantity Surveyors 6 (2) (2006) 31–43. [20] T. Hegazy, T. Ersahin, Simplified spreadsheet solutions I: subcontractor information system, ASCE Journal of Construction Engineering and Management 127 (6) (2001) 461–468. [21] Y.C. Shiau, T.P. Tsai, W.C. Wang, M.L. Huang, Use questionnaire and AHP techniques to develop subcontractor selection system, International Symposium on Automation and Robotics in Construction, 19th (ISARC) Proceedings, National Institute of Standards and Technology, Gaithersburg, Maryland, 2002, pp. 35–40. [22] V. Albino, A.C. Garavelli, A neural network application to subcontractor rating in construction firms, International Journal of Project Management 16 (1) (1998) 9–14. [23] Z. Hatush, M. Skitmore, Contractor selection using multicriteria utility theory: an additive model, Building and Environment 33 (2–3) (1998) 105–115. [24] M. Sonmez, G. Holt, J.B. Yang, G. Graham, Applying evidential reasoning to prequalifying construction contractors, ASCE Journal of Management in Engineering 18 (3) (2002) 111–119. [25] J.S. Russell, M.J. Skibniewski, Decision criteria in contractor prequalification, ASCE Journal of Management in Engineering 4 (2) (1988) 148–164. [26] D. Singh, R. Tiong, A fuzzy decision framework for contractor selection, ASCE Journal of Construction Engineering and Management 131 (1) (2005) 62–70.
[27] A. Elazouni, F. Metwally, D-SUB: decision support system for subcontracting construction works, ASCE Journal of Construction Engineering and Management 126 (3) (2000) 191–200. [28] M. Rahman, M.M. Kumaraswamy, Potential for implementing relational contracting and joint risk management, ASCE Journal of Management in Engineering 20 (4) (2004) 178–189. [29] F.E. Edum-Fotwe, A.D.F. Price, A. Thorpe, Transformed financial ratio models for improved contractor evaluation, Proc., 1st International Conference on Construction Project Management, Nanyang Technological University, Singapore, 1995, pp. 559–567. [30] E.J. Jaselskis, J.S. Russell, Risk analysis approach to selection of contractor evaluation method, ASCE Journal of Construction Engineering and Management 118 (4) (1992) 814–821. [31] L.G. Crowley, D.E. Hancher, Evaluation of competitive bids, ASCE Journal of Construction Engineering and Management 121 (2) (1995) 238–245. [32] J.S. Russell, Constructor prequalification-choosing the best contractor and avoiding constructor failure, ASCE Press, New York, 1996. [33] M.M. Kumaraswamy, Contractor evaluation and selection — a Hong Kong perspective, Building and Environment 31 (3) (1996) 273–282. [34] A.M. Alsugair, Framework for evaluating bids of construction contractors, ASCE Journal of Management in Engineering 15 (2) (1999) 72–78. [35] L.F. Alarcon, C. Mourgues, Performance modelling for contractor selection, ASCE Journal of Management in Engineering 18 (2) (2002) 52–60. [36] J.S. Russell, M.J. Skibniewski, QUALIFIER-1: contractor prequalification model, ASCE Journal of Computing in Civil Engineering 4 (1) (1990) 77–90. [37] J.S. Russell, M.J. Skibniewski, D.R. Cozier, QUALIFIER-2: knowledgebased system for contractor prequalification, ASCE Journal of Construction Engineering and Management 116 (1) (1990) 157–171. [38] G.D. Holt, P.O. Olomolaiye, F.C. Harris, A conceptual alternative to current tendering practice, Building Research and Information 21 (3) (1993) 167–172. [39] G.D. Holt, P.O. Olomolaiye, F.C. Harris, Factors influencing U.K. construction clients' choice of contractor, Building and Environment 29 (2) (1994) 241–248. [40] G.D. Holt, P.O. Olomolaiye, F.C. Harris, Applying multi-attribute analysis to contractor selection decisions, European Journal of Purchasing and Supply Management 1 (3) (1994) 139–148. [41] G.D. Holt, P.O. Olomolaiye, F.C. Harris, Incorporating project specific criteria and client utility into the evaluation of construction tenderers, Building Research and Information 22 (4) (1994) 214–221. [42] G.D. Holt, P.O. Olomolaiye, F.C. Harris, Evaluating pre-qualification criteria in contractor selection, Building and Environment 29 (4) (1994) 437–448. [43] G.D. Holt, P.O. Olomolaiye, F.C. Harris, Application of an alternative contractor selection model, Building Research and Information 23 (5) (1995) 255–264. [44] G.D. Holt, Which contractor selection methodology? International Journal of Project Management 16 (3) (1998) 153–164. [45] C.H. Ko, M.Y. Cheng, T.K. Wu, Evaluating sub-contractors performance using EFNIM, Automation in Construction 16 (4) (2007) 525–530. [46] M.J. Skibniewski, M. Abduh, Web-based project management for construction: search for utility assessment tools, Proceedings of INCITE 2000, Hong Kong Polytechnic University, Hong Kong, 2000, pp. 56–77. [47] Y. Zhu, R.R.A. Issa, Viewer controllable visualization for construction document processing, Automation in Construction 12 (3) (2003) 255–269.