An accelerated subcontracting and procuring model for construction projects

Automation in Construction 11 Ž2002. 105–125 www.elsevier.comrlocaterautcon

An accelerated subcontracting and procuring model for construction projects H. Ping Tserng ) , Pao H. Lin Department of CiÕil Engineering, National Taiwan UniÕersity, Taipei 10617, Taiwan Accepted 10 April 2001

Abstract Considering the characteristics of highly specialized corporation in the construction industry, it’s crucial to select appropriate subcontractors to implement specific subprojects. In this research, the overall subcontracting supply chain of a construction project is considered as a global procurement system and an optimal combination of subcontractors can be obtained within this system. Combining the quick response mechanism of information technology with portfolio theory in financial management, an integrated XML ŽeXtensible Markup Language. of Accelerated Subcontracting And Procuring ŽASAP. model was proposed. The ultimate goal of this study is not only to develop a web-based decision support system for general contractors to accurately decide an appropriate trade-off between risk and profit for different combinations of subcontractors, but to take the subcontracting and procuring process into re-engineering through omnipresent Internet. q 2002 Elsevier Science B.V. All rights reserved. Keywords: Procurement; Subcontracting; SGML; XML; E-commerce ŽEC.; Supply chain management ŽSCM.

1. Introduction In the midst of our highly competitive, globalizing industrial system, business turn toward making the best use of their superior position for competitive advantages, in order to promote their competitiveness and to increase beneficial advantages in specific industry w1x. Because of this, in the early 1990s business downsizing, reengineering w2x, restructuring and other practices became increasingly popular. )

Corresponding author. Tel.: q886-2-2364-4154; fax: q886-22366-1640. E-mail addresses: [email protected] ŽH.P. Tserng., [email protected] ŽP.H. Lin..

Many businesses maintained aspects of their organizations that reflected their core competencies w3x within the larger marketplace, while the remaining non-core or relatively non-profitable manufacturing operations, were all moved as far as possible to outsourcing w4x or subcontracting to utilize resources already available on the market, in order to diversify against risk in the industry and marketplace, reduce operation costs, secure competitive advantages and search for the most suitable profit base. Starting from this situation and looking toward specialized technological divisions of labor, the construction industry for some time has shown to have a highly fragmented subcontracting structure. There have been a number of studies on the subcontracting

0926-5805r02r$ - see front matter q 2002 Elsevier Science B.V. All rights reserved. PII: S 0 9 2 6 - 5 8 0 5 Ž 0 1 . 0 0 0 5 6 - 5

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strategies and organizational styles of construction firms, including from the perspective of Williamson’s economic organizational models based on transaction-costs theory w5x to mutual-benefit analysis of specifically designated transaction styles, such as Love w6x and Weston and Gibson w7x on Apartnering,B Krippaehne’s Avertical business integrationB w8x, Kwok and Hampson w9x on Astrategic alliances,B Eccles’s work on Aquasi-firmsB w10x, and so on. Furthermore, there are so many research and investigation results, like Gray and Flanagan w11x and Hinze and Tracey w12x, which demonstrate that using the way of outsourcing to acquire necessary resources and to implement specific subproject has been the main developing stream and dominantly competitive strategy. Further citations from Ball w13x, Millman w14x, Matthews et al. w15x, and Nobbs w16x also point that: for the time being, a large majority of engineering functions and values of a project are carried out by specialized engineering firms and general contractors have been playing the roles of project coordinator and manager more than the actual builders that employ direct labor to undertake construction work. Because of this, in today’s situation where those carrying out large projects are faced with an environment that places great emphasis on subcontracting, the importance of selecting appropriate subcontractors is unquestionable. However, while many current researches take the relationships between general contractor and owner as the focal point for performance management in construction projects, they rarely address questions of how to select subcontractors, how to form criteria for selecting subcontractors, or how to create complete supply links between subcontractors w17x. On the subject of subcontractor selection, Ashraf and Fikry w18x put forth a decision-making support system that allows contractors to simulate calculations for the best work item or the best proportion of the subcontracting. This system takes the lowest total project cost to the contractor as the objective function, but it has no way to take into account the interactive business relationships between subcontractors, and the risk to quality control caused by low-quality subcontractors. Mohan and Matthews w17x put forth an improved system for selecting and partnering with subcontractors. That research first put all of the multiple partnering relationships be-

tween subcontractors into a complete package to make a comprehensively integral evaluation. However, by depending on this process the general contractor not only must go through the usual steps of evaluating the subcontractor’s licenses and qualifications, but also must undertake three face-to-face interviews before making a final decision. Unfortunately, this selection system is obviously far from ideal for practical use in projects that require multiple subcontractors under heavy time constraints. In the traditional subcontracting process, for reasons of information asymmetry and uncertain factors intervened by people, the selection of subcontractors frequently cannot be controlled well, easily resulting in inefficient management and poor project performance. However, the rise of the Internet and e-commerce w19x has thoroughly changed the traditional market’s business rules and has brought a revolution in transaction practices. The use of Internet-based technology initiatives makes the exchange of information simple, fast, accessible, and accurate, and brings a new, pivotal opportunity and force to development of the construction industry w20,21x. In the past few years, research on the adaptation and use of information technology ŽIT. integrated with the Internet in the construction industry, such as work by Zipf w22x, Hudgins and Chang w23x, Ahmad w24x, and others w25,26x, has emphasized web technology’s helpfulness and promoted its usefulness for managing project performance, simplifying operations processes and document management, as well as organizing communication and coordination between project participants. Research regarding Internet -based electronic purchasing, such as the research report on procurement practices and trends by Segev et al. w27x, which covered the results from surveys and interviews with over 80 companies, have included such topics as Internet-based procurement technological processes, technology, utilization, relationship of supply chain as well as e-commerce, but have in no way been undertaken with the specific needs of the construction industry in mind. Recently, Lin and Tserng w28x proposed a preliminary model using IT to establish a standardized environment to accelerate the processes of subcontracting construction project. Based on the above background analyses, it can be shown that, by using the latest IT initiatives, one

H.P. Tserng, P.H. Lin r Automation in Construction 11 (2002) 105–125

cannot only manage what were once unbearably complicated practices, but also through the essential character of the information transparency, minimize past internal impediments to the market by human factors among participants, put an end to traditionally uncertain characteristics in business practices and inadequate sharing of information among parties, guard against minor and speculative business practices, and furthermore can minimize overall business transaction costs. And only through the transformational processes of information standardization and the implementation of IT environment will it be possible to purify the essence of construction industry and improve the quality of policy decisions.

2. Problem statements and research objective Traditionally, the practice for selecting subcontractors was to take the way of Achoosing while workingB on the project, especially those who were set to work together with or those with whom one had already done business, which gave rise to Aquasi-firmB w10x sub-structures. This kind of practice certainly has its benefits, including flexibility, stability, mutual trust, and decrease of transaction and search costs. However, after some investigation and analysis, this traditional practice contains, at a minimum, the following problems and questions. Due to long-term cooperative relations between the general contractor and subcontractor, the force of personal relationships can easily turn into a managerial bottleneck; additionally, the more the general contractor depends on the technical skills of the specific subcontractor, the more difficult it becomes to control costs, and the more necessary it becomes to depend on specific producers; all of these factors make it less likely that new technological skills or ideas will be adopted. Due to the speed with which most projects are carried out, most subcontractors are selected only when the time for their portion of the work is near, to the point that the time used for giving out contracts becomes excessively short; aside from hastiness and the difficulty in making the best choice, recognition and communication may not be adequate, and this can easily lead to conflicts between subcontractors on the site w12x. v

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Because of factors related to limitations on finance, manpower, time, and information in the traditional procurement, there is often no way to effectively expend the sample space to try out new clients, which can give rise to inefficiency in subcontractor selection and negotiation processes. The traditional way to subcontract a project does not allow for thorough evaluation of the interdependence of various participating entities in each project, and generally cuts each specific project into several completely independent subcontracts. Under the limitations of a rigidly predetermined work duration, the lowest bid is usually the main criterion for final decisions of each subcontract. Hence, because a general contractor might not consider the entire supply chain of projects, what are individually optimal combination may not necessarily result in the best global outcome. Subcontracting selection and planning processes often lack objective decision-making and reliable standards, making it impossible during initial planning to predict overall performance and risk levels involved in carrying out a project. Therefore, this research, following the macro viewpoint of systematization, brings all selected combination and technological processes of subcontracting toward project performance of degrees on influence, under control and evaluation. In another area, while current developments in electronic procurement systems are mostly focused on a simple conversion of traditional bidding processes Žhandled by people. into electronic systems, this research’s emphasis lies not only in the digitalization, but also in the development of IT environment and standardization of these processes. By standardizing the subcontracting selection process, businesses can integrate with their own Enterprise Resource Planning ŽERP. system to gain further benefits from their resources, and take a step toward platform systematization for different organizations and work units to meet their long-term goals. Based on the comments above, the objectives of this research are set up as follows. Taking advantage of IT initiatives of e-commerce to combine with the use of electronic information exchange standards Ži.e., eXtensible Markup Language, XML. to propose an Internet-based online subcontract bidding and negotiation architecture. v

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v

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Considering the aspects of time, profit, and risk to integrate with the investment portfolio theory, to develop an ASAP decision support system which can perform the scenarios simulation for general contractors to easily decide an appropriate trade-off between risk and revenue for different subcontracting combinations. The use of this web-based planning system makes it possible for the general contractors with an overall and wide-ranging perspective to have a insight about market information, to respond quickly to the market’s changing needs, and gain time-based competition capabilities. This model can be applied to the simulation of subcontracting cost before bidding and the subcontracting decision support after acquiring a bid. v

3. Construction information technology and standards The ASAP model is provided with the functions of real-time decision making and endowed with capabilities similar to the Internet bidding market. Due to the potential for a high number of subcontractors on the market, every business usually employs a certain kind of software system to manage and record documents and information Že.g. MS Word, Lotus WordPro or Adobe PDF format.. The formats and standards of each system are different, and without format conversion, it is not easy to share and exchange documents and information. Furthermore, since their markup methods are not the same, it is difficult to reuse and repurpose existing documents, and as a result, a given document’s scope of usability is highly limited, which reduces the possibility for leveraging and adding value to the information contained in the document. Only after going over processes of standardization, businesses can combine their individual ERP’s to reuse and repurpose information, can also extend this information toward uses in Business Process Reengineering ŽBRP., to make operating processes more rational, efficient, and exquisite. Consequently, the establishment of common standards to communicate is in fact the basis of ASAP model. The following consists of several information standards for document delivery and exchange.

3.1. Standard Generalized Markup Language (SGML) Currently, the formats and markup of general document management systems are mixed with structure, content, and display rules together, and as a result, if a user wants to find a specific piece of information within the document structure, it can become quite difficult owing to no rule existing for how the document is structured. In light of such problems in document standardization, SGML was adopted as a standard by the International Organization for Standardization ŽISO. in 1986. SGML is an international standard for the definition of device-independent and system-independent methods of representing texts in electronic form. The structure, content, and display of documents are separated in SGML, and the Document Type Definition ŽDTD. is used to define all of the relationships between every type of markup standard in specific document style. Different systems need only to follow this common standard in order to unify the data format and to undertake cross-platform information exchange, sharing, and reuse, thus breaking the limitations of previous software and hardware systems. However, the largest problems of SGML lie in the difficulty in mastering all of its complexities and the large-size volume, the lack of support software, and cumbersome transportation in the Internet. As a result, most businesses cannot afford to invest the human and financial resources required to maintain an SGMLbased document creation and management system w29x. 3.2. eXtensible Markup Language (XML) Due to problems related to the unwieldy complexities of SGML and its lack of Internet capability, in late 1996 the World Wide Web Consortium ŽW3C. put forward the XML standards. XML was designed with 10 major goals w30x in mind, the most important of which was to determine a set of global Internet information standards that would allow for global Internet-based document transmission and management w31x. XML is essentially a descendant of SGML, and therefore inherits the flexibility and strengths of SGML, while at the same time it casts off or simplifies complex features and little-used portions of

H.P. Tserng, P.H. Lin r Automation in Construction 11 (2002) 105–125

SGML, which makes XML document creation faster, simpler, and easier to understand. The first goal of XML is weighted toward materials that can be transferred directly to and used on the Internet, and its design principles are to allow general web-browser to be able to read XML documents, including all kinds of images, hyperlinks and multimedia items, among others. Additionally, XML can express complicated information structures, and can define special fields and customized markup languages that HTML is unable to manage. A simple example in Fig. 1 shows the document structure of XML and HTML. We can find that XML utilizes variable tag name to AdescribeB information and to organize document, and possesses the great potential to communicate with database. While HTML is constrained to specific tag name, such as - h ) and - p ) to just AdisplayB information and can hardly be expected to use these undistinguished tags to access database. XML can also rely on DTD as a standard for document transmission, but its requirements for collocation with DTD also provides for choosing whether or not to use it. In 1999 W3C brought out an idea for XML Schema, which was directed toward the difficulties in using DTD, especially the incompatibilities between DTD and XML grammar, the limitations of DTD surrounding its insufficiently precise datatype, and the difficulties in creating complex logic structures of documents. Because XML Schema can im-

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prove the soundness of data identification, maintain logical structure of documents and increase their readability, this research uses XML Schema as its developing standard scheme for document transmission and exchange. At the moment, on the international level the aecXML w32x organization is specially working on AEC Žarchitecture, engineering, and construction. industry information exchange standardization, and has formulated aecXML Schema as part of its plans for a complete common standardized Language for construction information exchange, whose contents would cover engineering projects, documents, organizations, resources, and other possible management and communication usage standards; its reach is quite wide-ranging, and opens the discussion on adoption of international standards. Although the development and usage of XML is still at an early stage, in terms of content management it maintains consistency, dynamic display, content reusability, and advantageous lack of any software requirements, and will make it indispensable with the global expansion of the Internet. 3.3. Electronic Data Interchange (EDI) EDI can be regarded as the grandfather of the electronic commerce. The appearance of EDI is for setting up a standard for data exchange, especially

Fig. 1. Document structure of XML and HTML.

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for different organizations and fields. There are two main developing streams in the most famous global EDI standards: the north American ANSI X.12 and European UNrEDIFACT w33x. In spite that EDI provides the wide advantages to uplift the competitiveness of business and industry, it has still not yet been popular and widely applied since 1960s up to date. There are so many reasons or constraints existing, such as: the initial set-up cost is expensive, the transportation media are limited, the establishment of standard is time-consuming, and only parts of automation are reached.

4. ASAP model 4.1. Theoretical foundation of ASAP model The ASAP model theoretical basis utilizes information technology integrated with quick response mechanisms of e-commerce, puts to use statistics and investment portfolio theory, takes all of the possible subcontractor combinations of bidding information into consideration and finally analyzes it as an expenditure loading distribution curve. This model assumes that: Ž1. for each project, the general contractor plans logical relationships between subprojects; Ž2. all parties offering and competing for bids have already been pre-qualified and recognized as qualified subcontractors; Ž3. the decision-making process considers the selection of subcontractors to be a process of investment portfolio, and each combination of subcontractors represents one certain kind of portfolio set in the market. ASAP model will automatically estimate the relative risk versus its profit according to specific Arisk basisB, which is assigned by the decision-maker at the beginning of subcontracting simulation. The aforementioned relative risks can be obtained by comparing the current project with well-performed historical project or professional experiences. There are three kinds of risk basis set up to assist the decision-maker. Basis on economic efficiency optimization: this criterion presumes the general contractor’s expenditure amount on specific project has nothing to do with project’s proceeding schedule. That is, the planned cost expenditure is uniform distribution, and there is no any additional variable cost need to be v

paid. This is based on the concept similar to resource leveling in order to reach the optimal economic efficiency. Basis on the internal demands and professional judgment: this criterion is subjectively assigned by decision-maker according to specific financial plans and professional judgement of the general contractor’s experience on certain project type. Basis on performance database of historical projects: the research of Continuous Assessment of Project Performance ŽCAPP. was performed by the American Construction Industry Institute ŽCII. in 1996 w34,35x. CAPP uses continuous or time-dependent variables to predict project cost and schedule outcomes from the start of detailed design through construction project completion. A continuous variable is defined as a time-dependent quantity whose value can be collected at several points during the course of a project. From the survey of 54 projects of 76 variables, CAPP demonstrates a significant difference between the AsuccessfulB s-curves and Alessthan-successfulB ones. Furthermore, CAPP also allows the decision-makers to refer to the manifestations of past projects’ s-curves and apply them to currently underway, evaluate whether current performance targets are moving in successful or losing directions, and in this way project managers can evaluate the mastery of the degree of the project’s level of cost control and possible relative risks. Due to the well-developed foundation of CAPP, completeness in assessing project performance, and its practical applicability, this project takes CAPP as the standard database for project performance evaluation and risk assessment. The ASAP input requirements for bidders include bidder’s basic resume, bid price, scheduling plan and, most importantly, the financial loading distribution curve, which is the dominant key factor to influence the bidding result for specific subproject. Besides, the risk basis is the required input for general contractor. ASAP will integrate all the possible situations of subcontracting combination for the whole project to analyze risk degree and reflect it on the plane of risk versus profit. Based on the theory of investment portfolio w36x, the efficient frontier can be graphed and established as shown in Fig. 2. The physical meaning of efficient frontier is that the subcontracting combination only located on the fronv

v

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111

Fig. 2. Efficient set of selecting subcontractors and risk decision-making.

tier is an efficient set of portfolio. It implies that any selection on the frontier curve general contractor can win the highest expected revenue under any specific risk degree or will suffer from the lowest risk under specific expected revenue. As for the final selection,

it will be dependent on the risk preference of the decision-maker. Theoretically, a decision-maker with risk-averse preference expects a group of utility indifference curve like Fig. 2, where each of them represents a specific utility level. Moreover, the effi-

Fig. 3. Architecture of ASAP system and data transformation.

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Fig. 4. Expression of risk basis and dispersion degree.

cient frontier can be regarded as the constraint curve to select the efficient subcontractor combination. Therefore, in order to get the most efficient solution, the decision-maker necessarily makes a compromise

between the efficient frontier and utility curve by adjusting one’s utility level to reach a tangent point, such as point O in Fig. 2. However, the efficient frontier is not a perfectly continuous curve in this

Fig. 5. The information flow of ASAP system.

H.P. Tserng, P.H. Lin r Automation in Construction 11 (2002) 105–125

model’s application, so the efficient combination set nearest to the tangent point can be the alternative of the optimal selection. 4.2. System architecture of ASAP model The ASAP model adopts the three-tier architecture which is widely applied in recent years as the developing system framework. The three-tier architecture combines the merits of concentration and client–server structure. It utilizes the property of separating user interface with business logic model, and reduces the dependence between application program and database. It is a very flexible and effective structure for database updating, renewing, and remodeling. Every client user needs only to open their

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web browser to use the system’s capabilities to retrieve all of the needed information online. The three tiers include the presentation, business logic, and data tiers. The presentation tier in ASAP is mainly composed by the Database Administrator ŽDBA. and common user interfaces. It is the media by which the user can communicate with the web server and database. The business logic tier operates the main application functions, such as computing, querying, and graphing. The data tier can directly retrieversave any information fromrto database. The ASAP system uses the Open Database Connection ŽODBC. as the end interface with database, and can use ACCESS, SQL Server and related supporting database software. The framework and processing flow are demonstrated by Fig. 3. The project and

Fig. 6. Schematic representation of ASAP approach for selection.

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H.P. Tserng, P.H. Lin r Automation in Construction 11 (2002) 105–125

bidding data of ASAP are all stored in a database, and in the data delivery process all use the XML format to envelop document, and therefore all data input and output must pass through the converting interface. The lower half of Fig. 3 illustrates the XML data management and conversion process, such as when data retrieved from the database has gone through the Active Server Pages ŽASP., and then after passing through the XML Parser, can then undertake the client data application, such as the collocation capabilities of XSL or HTMLrCSS to display documents and other specific development. 4.3. Risk calculation methods of ASAP model This research will take the dispersion degree as the quantitative index to identify risks and establish

mathematically analytical model and thereby defines dispersion risk ŽDR. as follows: the difference between the expenditure loading curve of specific subcontracting combination and the risk basis curve setup by decision-maker at an arbitrary time-point for a project underway. Because different subcontracting combinations will cause different work duration and capital expenditures, in order to analyze and compare different combinations at the same scale, it is necessary to normalize every outcome of subcontracting combinations. This normalization process involves converting the aforementioned capital expenditure curve value into a dimensionless percentage value on both developing axes. In this way, all subcontracting combinations can be compared on the same Apercentage scaleB. This is shown as Fig. 4 in which horizontal axis represents the time percentage

Fig. 7. Flow chart of solving process for ASAP system.

H.P. Tserng, P.H. Lin r Automation in Construction 11 (2002) 105–125

Fig. 8. The object modeling technique expression for ASAP schema.

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H.P. Tserng, P.H. Lin r Automation in Construction 11 (2002) 105–125

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of degree of completion for a project, that is, 0% equal to the beginning of construction or procurement, while 100% equal to the end of construction, and vertical axis is the percentage of capital expenditure to total cost of a project along the degree of its completion. Besides, since the loading curves of capital expenditure of EST Žearly start time. and LST Žlate start time. are not distributed identically, this research will take the average value of the EST and LST as the representative curve to proceed the normalization. On the other side, dispersion risks in practice will give rise to positive or negative deviation, so this paper will take all dispersion degrees in squared form. Following the theoretical foundations above, ASAP uses the following mathematical model to proceed with detailed computation. First, ASAP model draws into a status matrix Ž N q 1. = n Ždefined as Eq. Ž1.. in which N represents the number of total subjects in whole project, n is the number of time units for project duration, f˜i Ž t . s w t i1 ,t i2 , . . . ,t i n x is a planned distributed series of capital expenditure from the subcontractor for arbitrary subproject i, and each element t i j Ž i s 1,2, . . . ., N; j s 1,2, . . . ., n. equals the planned capital expenditure in each time unit if work is done; and equals zero for no work done. f˜1 Ž t . f˜2 Ž t . ... FŽ Nq1.=n ' f˜3 Ž t . ... ˜f N Ž t .

N

f˜S Ž t . s

Ž 2.

is1

°t ~

Ý f˜i Ž t .

S1 s t 11 q t 21 q . . . qTN 1 t S 2 s t 12 q t 22 q . . . qTN 2 ... t S n s t 1 n q t 2 n q . . . qTN n

Ž 3.

¢

So, if we define Eq. Ž4. as the total amount of cost expenditure for the specific subcontracting combination, and set the average series as Eq. Ž5., where f˜S Ž t . ES and f˜S Ž t . LS represent the expenditure loading distribution based on the early start time and late start time, respectively. n

Ss

Ý tS i

Ž 4.

is1

f˜S Ž t . ave s

Ž f˜S Ž t . ES q f˜S Ž t . LS .

Ž 5. 2 According to the definition of normalization mentioned above, Eq. Ž5. can be normalized into a distribution with dimensionless ratio value as the form of Eq. Ž6.. f˜S Ž t . norm s

f˜S Ž t . ave

Ž 6. S In addition, based on the defined DR, the DR at arbitrary time-point can be computed as Eq. Ž7. in squared form, where S˜Ž t . is the distribution of normalized risk basis for comparison.

f˜S Ž t .

'

The matrix Ž N q 1. = n represents the complete working status and capital expenditures for the whole project. Moreover, in Eq. Ž1., f˜S Ž t . is the summation of all series f˜1 Ž t ., f˜2 Ž t ., f˜3 Ž t ., . . . , f˜N Ž t ., that is, the capital expenditure loading curve under a certain subcontracting combination, and can be denoted as Eq. Ž2., which satisfies the limitation of Eq. Ž3..

t 11

t 12

...

t1 j

...

t1 n

t 21

t 22

...

t2 j

...

t2 n

... t i1

t i2

...

ti j

...

ti n

... tN 1

tN 2

...

tN j

...

tN n

t S1

tS 2

...

tS j

...

tS n

2

d 2 Ž t . s Ž f˜S Ž t . norm y S˜Ž t . . Ž 7. Finally, the total dispersion risk in the normalized duration of any project can be shown as Eq. Ž8., in which dtotal is the total DR; f˜S Ž t . norm and S˜Ž t . are described as before. n 2 dtotal s

Ý Ž f˜S Ž t . norm y S˜Ž t . .

2

Ž 8.

ts1

Ž 1.

This research takes every 5% of both total cost and time span as the computing step to get the total

H.P. Tserng, P.H. Lin r Automation in Construction 11 (2002) 105–125

risk. So the total steps n will be equal to 20. Fig. 4 shows at the specific time-point j the expression of dispersion risk between a certain combination of capital expenditure and the standard curve of risk basis. There are two kinds of risk basis curves shown in the figure, namely, curve S1 derived from CAPP database or set-up by professional requirement, while curve S2 is a uniformed distribution Žequal to a specific constant. with no variable arrangement. It is obvious that the influence degree of the same dispersion risk to the performance of a project is not always the same at different time-point along a project schedule. So a weight function will be allowed to induce in an ASAP model to evaluate the risk degree at a different time schedule. Moreover, Eq. Ž8. can be further changed to Eq. Ž9., in which w Ž t . is the weight function set up by the decisionmaker. n

d t2o t al s

Ý Ž f˜S Ž t . norm y S˜Ž t . . w Ž t .

2

Ž 9.

ts1

4.4. Information flow of ASAP model The key design concept of ASAP system is to work from the perspective of construction industry

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contractors to create a completely portable web-based subcontracting planning and support system. On the other hand, a very fair and effective virtual transaction market environment or mechanisms is also established for interested bidders. The data processes of ASAP model as illustrated in Fig. 5 are made up of the following key steps: Ž0. The general contractor prepares the relevant electronic documents and forms for accepting bids. Ž1. The general contractors advertise the project information and make a call for relevant bids through Internet. Bidding information can be advertised on a relevant e-market web site or on a site specifically prepared by the general contractor. Ž2. Interested subcontractors download the DTDrSchema tender forms. Ž3. Subcontractors store and display relevant bid information using their own information system. Ž4. Interested subcontractors submit XML tender forms via the Internet. Ž5. The general contractor receives each bid information of subcontracting through the Inter-

Fig. 9. The logic relationship network for testing case.

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Table 1 The quotation information of bidders for the testing case

A A A B B C C D D D D E F F F G G H I I J

1 2 3 1 2 1 2 1 2 3 4 1 1 2 3 1 2 1 1 2 1

51 000 48 900 53 000 42 500 44 200 35 000 37 500 11 200 15 500 12 350 14 000 1200 27 500 29 000 26 000 5000 6500 2800 6300 5200 2750

12 10 10 17 19 15 12 13 11 13 10 6 10 12 13 6 6 5 4 5 4

2000 1000 2000 500 200 100 500 100 300 350 1000 100 2000 1000 1000 1000 500 800 1500 1000 1000

3000 3000 5000 1000 1500 400 1000 200 500 400 2000 200 3000 4000 3000 1200 1500 1000 2500 1500 750

5000 5000 5000 1200 1500 600 2000 500 800 1000 3000 400 5000 5000 4000 1500 2000 400 1300 2000 500

6000 8000 9000 10 000 7000 9000 8000 5000 6000 10 000 9000 6000 1500 2000 3000 4000 2500 3500 4000 6000 1400 3000 5000 6500 4000 5000 7000 8000 700 1500 1700 1300 1000 1400 2000 5000 1700 2300 2250 2000 2000 1000 1000 1000 300 100 100 6500 2000 2000 2000 3000 2000 2000 2000 5000 4000 2000 1000 500 500 300 1500 800 200 400 200 1000 400 300 500

u8

u9

u10

u11

u12

3000 5000 4000 5000 5000 5500 5000 1200 2500 1350 1000

2000 4000 3000 5300 3000 4500 3000 1000 1500 500 1000

1000 1900 3000 5000 2500 2500 1000 1000 400 200 1000

1000 1000

u13

u14

u15

u16

u17

u18

u19

3500 3000 2000 2000 1500 1000 1000 2000 2000 1500 1500 1500 1500 1500 1500 1500 1500 1000 1000 1000 1000 800 200 1000 700 300 100 100 100 100

2000 2000 1000 2000 2000 2000 2000 2000 1000 1000 1000 1000 1000 1000

H.P. Tserng, P.H. Lin r Automation in Construction 11 (2002) 105–125

SubBidder Tender- Duration Cost loading distribution per unit time step project price u1 u2 u3 u4 u5 u6 u7 ID

H.P. Tserng, P.H. Lin r Automation in Construction 11 (2002) 105–125

net server, and begins a simulated analysis of all combined subprojects. Ž6. During the simulated calculation process, messages are processed between the business logic and data tier. Ž7. ASAP chooses the most advantageous package of subcontractors according to the preset goals and standards of the general contractors. Ž8. Following the results of the analysis, contracts are awarded to and determined with the selected subcontractors through XML data transfer. Following these steps finally achieves a complete subcontract procuring and planning process. This system is designed for use by both general contractors and subcontractors, so it will automatically lead different users to two separate main web pages, clearly separating and fulfilling the needs of different users along with their varying permission authorities.

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Browser. As stated above, this research uses the Schema developed by aecXML as the basis for a standard schema, but certain specially required information which are used in this model and have not been defined by aecXML are set in the naming conventions of aecXML Schema Guidelines w32x. Because an XML document is hierarchic in structure, it is composed of the continuous development of parent–child relationship. XML possesses the very similar ideas of the objects-oriented extension, including class, attribute, aggregation, and message relation structure, so it is ideal to use the Object Modeling Technique ŽOMT. w37x to demonstrate the architecture of XML Schema. The structure of ASAP system’s Schema integrated with aecXML can be shown as Fig. 8. The schema of this system is somewhat complicated, so only a part of this schema is extracted Žsee Appendix A..

6. Illustrative example 4.5. Selection criteria of ASAP system ASAP decision support system cannot only select the optimal combination of subcontractors by the risk preference of decision-maker, but also provides other varieties of selection criteria or functions: such as selection for the lowest price and the shortest duration, direction of the optimal project scheduling and cost controlling, the probability analysis of possible critical path, and so on. The input, output, and schematic representation of ASAP system are expressed as Fig. 6. Furthermore, the flow chart in Fig. 7 shows detailed steps for ASAP approach to find the optimal selection.

5. Implementation of ASAP system The development of ASAP system is constructed on the software platform of MS Windows NT Server 4.0 and PCrWorkstation. Except for the application of CAPP database, the database end can adopt MS ACCESS or SQL Sever as the accommodation of bidding information. The developing softwares of interface include Visual Basic, Javascript, Active Server Pages, and integrated with XML and Web

A project contains 10 subprojects, the logic relationships between subprojects are composed by SS ŽStart to Start., SF ŽStart to Finish., FS ŽFinish to Start., and FF ŽFinish to Finish., four kinds of relationship constraint that are illustrated in Fig. 9. The basic tender information from every interested bidder via the Internet can be collected as in Table 1, in which the cost loading distribution is a very important and required information proposed by each

Table 2 Scheduling result of a sample calculation Žfor the combination set of maximum profit. Projectrlag time

Duration

ES

EF

LS

LF

Critical

A B C D E F G H I J

10 17 15 13 6 13 6 5 5 4

0 3 8 2 15 15 23 27 30 35

10 20 23 15 21 28 29 32 35 39

0 3 14 8 21 21 29 27 30 35

10 20 29 21 27 34 35 32 35 39

Yes Yes No No No No No Yes Yes Yes

H.P. Tserng, P.H. Lin r Automation in Construction 11 (2002) 105–125

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Table 3 Illustration of deriving dispersion risk of a sample calculation Žfor the combination set of maximum profit. Column w1x: duration of each time step derived from scheduling calculation. Column w2x: the corresponding time percentage to column w1x Ži.e., 0.0256 s 1r39.. Column w3x: original total cost loading distribution in each time step according to the scheduling calculation. Column w4x: cumulative cost distribution Ži.e., s-curve. of column w3x. Column w5x: every time step in 5% of total duration. Column w6x: the interpolation value in 5% time step, which is interpolated from column w2x, w4x and w5x, i.e., 3850 s 1000 q Ž4000 y 1000.)wŽ0.05 y 0.0256.rŽ0.0513 y 0.0256.x. Column w7x: cost loading of every 5% time step from the breakdown of column w6x Ži.e., 12 040 s 15 890 y 3850.. Column w8x: the normalize percentage value of cost loading from column w7x Ži.e., 0.0213 s 3850r180 550.. Column w9x: the standard of each 5% time step for risk comparison, which is set up by the decision-maker. Column w10x: computation result of the square of dispersion risk by column w8x and w9x Ži.e., 0.0001282 s Ž0.0213 y 0.01. 2 .. Process of computing duration and loading

Normalization process

DR calculation

w1x

w2x

w3x

w4x

w5x

w6x

w7x

w8x

w9x

w10x

Duration

Time step

Oriloading

S-curve

5% Time step

5% S-curve

5% loading

Normalize

Standard

Risk

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39

0.0256 0.0513 0.0769 0.1026 0.1282 0.1538 0.1795 0.2051 0.2308 0.2564 0.2821 0.3077 0.3333 0.3590 0.3846 0.4103 0.4359 0.4615 0.4872 0.5128 0.5385 0.5641 0.5897 0.6154 0.6410 0.6667 0.6923 0.7179 0.7436 0.7692 0.7949 0.8205 0.8462 0.8718 0.8974 0.9231 0.9487 0.9744 1.0000

1000 3000 5050 7600 10 250 9550 7250 7850 7750 6800 6050 6850 7750 7200 7100 6100 6650 6150 6400 6400 4950 4300 4850 4450 4500 3800 2300 2550 2150 1400 2500 2950 2750 1150 450 1000 750 500 500

1000 4000 9050 16 650 26 900 36 450 43 700 51 550 59 300 66 100 72 150 79 000 86 750 93 950 10 1050 107 150 113 800 119 950 126 350 132 750 137 700 142 000 146 850 151 300 155 800 159 600 161 900 164 450 166 600 168 000 170 500 173 450 176 200 177 350 177 800 178 800 179 550 180 050 180 550

0.05

3850

3850

0.0213

0.01

0.0001282

0.1

15 890

12 040

0.0667

0.01

0.0032132

0.15

35 018

19 128

0.1059

0.02

0.0073857

0.2

49 980

14 963

0.0829

0.02

0.0039529

0.25

64 400

14 420

0.0799

0.03

0.0024867

0.3

76 945

12 545

0.0695

0.05

0.0003796

0.35

91 430

14 485

0.0802

0.07

0.0001046

0.4

104 710

13 280

0.0736

0.07

0.0000126

0.45

117 183

12 473

0.0691

0.1

0.0009560

0.5

129 550

12 368

0.0685

0.12

0.0026523

0.55

139 635

10 085

0.0559

0.12

0.0041143

0.6

148 630

8995

0.0498

0.1

0.0025180

0.65

157 130

8500

0.0471

0.08

0.0010838

0.7

162 665

5535

0.0307

0.05

0.0003742

0.75

166 950

4285

0.0237

0.05

0.0006900

0.8

171 090

4140

0.0229

0.03

0.0000500

0.85

176 373

5282

0.0293

0.03

0.0000006

0.9

177 900

1527

0.0085

0.02

0.0001332

0.95

179 575

1675

0.0093

0.01

0.0000005

1

180 550

975

0.0054

0.01

0.0000212

Budgets 190 000, Total cost s 180 550, Profit % s ŽBudgety Total cost.rBudgets Ž190 000 y 180 550.r190 000 s 0.049737 Dispersion Risk s sum of column w 10 x s '0.03026 s 0.1740

'

S s 1.0000

S s 0.03026

H.P. Tserng, P.H. Lin r Automation in Construction 11 (2002) 105–125

bidder. Through the preplanning process of resource usage for specific bidding subproject, one can obtain the cumulative expenditure curve Žs-curve. and a further breakdown to the cost loading distribution in every time step. There are 576 possible combinations of subcontractors in this testing example, and the internal risk basis for comparison is set according to the specific historical experience. The general contractor’s budget cost is 190 000 Žmoney unit.. Tables 2 and 3 illustrate a sample calculation for the subcontractor combination of maximum profit according to the steps of the flow chart in Fig. 7. Table 2 shows the scheduling result, and Table 3 further demonstrates the process of computing total loading curve and profit, the normalization process, and finally derives the outcome of dispersion risk for the combination set. From the automated computation and iteration process of the system, the portfolio results of every feasible set can be obtained and graphed in the plane of risk versus profit as Fig. 10, in which the maximum profit and the least risky selection are denoted as A and B, respectively, on

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the efficient frontier curve. In this bid simulation, the maximum possible profit percent is 4.97%, much higher than the average profit Žjust count the positive samples. 1.43%; the total duration of this testing case is 39 Žtime unit.. There are 321 samples with positive profit, while the other 255 combinations of subcontractor will not be taken into consideration owing to their being of no benefit. Furthermore, the average dispersion risk is 0.1810 with standard deviation 0.0102, while the maximum profit combination possesses the risk of 0.1742. Part of the results are shown in Fig. 11. Because it is less than the average risk and inside one standard deviation, it can be regarded as a moderate selection in risk consideration. There are still several efficient combinations which have profits greater than the average and can be candidates for selection in the efficient frontier. Fig. 12 shows the capital expenditures distribution for the specific combination of maximum profit, and it can be referred by the general contractor to set up the financial planning. Fig. 13 shows the optimal scheduling bar chart for early start and late start

Fig. 10. The distribution of risk versus profit and efficient frontier for testing case.

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H.P. Tserng, P.H. Lin r Automation in Construction 11 (2002) 105–125

Fig. 11. The result of subcontracting simulation for testing case.

Fig. 12. The distribution of expenditure loading under maximum profit for testing case.

H.P. Tserng, P.H. Lin r Automation in Construction 11 (2002) 105–125

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Fig. 13. The bar chart for selection of maximum profit for testing case.

situations under maximum profit, where the critical path is A–B–H–I–J, with the total duration of 39 Žtime unit.. Moreover, the probability analysis of the critical path shows that path AA –B–H–I–JB is over 96% probable to be critical, so it is natural for the general contractor to pay more attention to these subprojects in order to control the overall performance.

7. Conclusion and future research Amidst rising trends of corporate specialization, the ability to properly manage subcontracting procurement is a key factor in maintaining competitiveness. The proposed ASAP architecture’s initial exploration of using IT to speed up construction projects’ subcontracting process, can help to improve the obvious limitations of traditional processes of selecting subcontractors, including the overly limited time for selection, high levels of uncertainty, and difficulties in judging quality. Aside from bringing together the perspectives of CAPP assessment model,

it also uses a historical case database to provide objective project performance standards to assess the total combined subcontracting risks, and applies XML document standardization technology to the production and management of bidding information in subcontracting, to create a web-based construction subcontracting risk assessment support system, for the standardization and economic optimization of the entire scheme of the highly interrelated subcontracting supply chain. Through this system and the development of examples, general contractors cannot only work in an environment without excessive time pressure to choose the most appropriate subcontracting supply chain, but control relevant risks and obtain anticipated profits. This formulation of this subcontract schema may be worth consideration in the future by related industries and organizations in the creation of standard schemes. The relevant illustrative example studies of ASAP system show that this architecture is certainly usable, and that the proposed ASAP model has completely transformed traditional thinking about subcontract procuring processes. It contains positive significance in its use of computeri-

H.P. Tserng, P.H. Lin r Automation in Construction 11 (2002) 105–125

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zation methods, and its beginnings in remaking the subcontracting procurement process. It will be possible to reduce the overall amount of time and capital required for procurement, and improve the ability to risk assessment. Most importantly, after being made into a widespread and workable process in the future, it will be effective in transforming traditional flaws of subcontractor selection, and greatly enhance the quality of subcontracting supply chain management and controlling the project performance. Due to the development in web platforms as the basis of its model architecture, it uses ASP language to carry out each subcontracting simulation for mathematical calculations. But the ASP language and its Internet-based application have certain constraints in computing functions compared with PC-based program language. Especially in the calculation of various combinations of subcontractors, the combinatorial explosion is an inevitable problem to face. In the calculation efficiency and solving algorithms, in the future it will be worth advanced consideration of the use of genetic algorithms or other methods to search for technological and theoretical improvements.

Acknowledgements The authors would like to acknowledge the National Science Council, Taiwan, for financially supporting this work under contract No. NSC-88-2211E-002-042.

Appendix A. Subcontract ASAP schema

²?xml versions A1.0B? : ²!–Generated by CEM Research Group2000 edi.1, National Taiwan University. Conforms to XML Data subset for IE 5– : ² Schema name s A subcontract – aecXML – prelim – v – 0081.xmlB xmlns s Aurn:schemas-microsoft-com:xml-dataB xmlns:dts Aurn:schemas-microsoft-com:datatypesB : ²ElementType names AaecXMLB contents AeltOnlyB order s AseqB : ²element types AProjectB minOccurss A0B maxOccurss A ) Br : ²element types ASubcontractorB minOccurss A0B maxOccurs s A ) Br :

²element types ACommunicationB minOccurss A0B maxOccurss A ) Br : ²rElementType: ²ElementType names AProjectB contents AeltOnlyB order s AseqB : ²AttributeType names AprojectIdB dt:types AidBr : ²attribute types AprojectIdBr : ²element type s ABuildingComponentB minOccurs s A0B maxOccurss A ) Br : ²element type s ATypeB minOccurs s A0B maxOccurs s A1Br : ²element type s ASizeB minOccurs s A0B maxOccurs s A1Br : ²element types ALocationB minOccurss A0B maxOccurss A1Br : ²element types ADescriptionB minOccurss A0B maxOccurs s A1Br : ²rElementType: ²ElementType name s ABuildingComponentB content s AeltOnlyBr : ²ElementType names ATypeB contents AtextOnlyBr : ²ElementType names ASizeB contents AtextOnlyBr : ²ElementType names ALocationB contents AtextOnlyBr : ² Elem entType nam e s A D escriptionB content s AtextOnlyBr : ²ElementType names ASubcontractorB contents AeltOnlyB order s AseqB : ²element types ACompanyB minOccurss A1B maxOccurs s A1Br : ²rElementType: ²ElementType names ABidB contents AeltOnlyBr : ²ElementType names ANameB contents AtextOnlyBr : ² ElementType name s A ContactPersonB content s AtextOnlyBr : ² ElementType name s A PostalAddressB content s AtextOnlyBr : ² ElementType name s A PhoneNumberB content s AtextOnlyBr : ²ElementType names AEmailB contents AeltOnlyB order s AseqB : ²ElementType names AUrlB contents AeltOnlyB order s AseqB : ... ... ²rSchema:

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