STRUCTURE DEVELOPMENT AND PERFORMANCE EVALUATION OF CONSTRUCTION KNOWLEDGE MANAGEMENT SYSTEM

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Introduction
Construction projects use the professional technology in civil engineering and relevant facilities to change land renovation and prevent calamity. This technique has not only close relation to the people's life, but also one of the key indexes in influencing the nation's public construction and economic development. Construction or civil engineering is a kind of basic necessary industry for each citizen's livelihood. Due to the characteristic of participants and tasks variety, this industry becomes highly requirement for collaboration and professional knowledge, especially in computer technology . Therefore, the enhancement of the competitiveness of a construction company is one of the most important strategic tasks in construction industry (Šiškina et al. 2009). For example, Fig. 1 shows the construction simulation of a high raise steel structure building with computer, Fig. 2 illustrates the scenario simulation of a dynamic fire disaster within a shopping mall, and Fig. 3 shows the calculation result of a simulation analysis. Up to today, it might because this industrial engineers' conventionalism trait, professional knowledge transferring and sharing did not work appropriately (Nonaka and Teece 2001;Bonner 2000;Park et al. 2009). Such situation makes the competitive ability of construction industry getting lower. Therefore, applying knowledge management in construction industry can improve its' operation with positive help. To illustrate the application effect and correct suitable management system, an appropriate evaluation model of performance result with constructional knowledge management system should be built.
This research illustrates how to use Windows 2003 Server IIS Ver. 5.0 to develop a prototype constructional knowledge management system. In this system, text, picture and image were edited by HTML schema. On the other hand, this system also applied ASP language to establish interactive web page. By applying of computer software and information technology, three-tier structural prototype of constructional knowledge management system was done. Because many researches focus on applying and conferring the guidance of structure system about knowledge management, only a little is aimed with performance evaluation of constructional knowledge management system (Chang et al. 2008;Lin and Shi 2004;Lin and Lin 2007;O'Leary 2002;Sayed et al. 2009). Therefore, this research develops a performance evaluation model to investigate the application result of constructional knowledge management system.

Development and current situation of construction industry in Taiwan
In the past 40 years, the global economy made big influence to the social economic development, resource allocation and quality of the life. From 1951 to 1969, due to the shortage of funding and labour, public construction projects in Taiwan had focused on improving the agriculture and light industry production. Then from 1971 to 1979, the government had developed 12 national construction projects. After that, the government continuously had developed 14 national construction projects from 1981 to 1989 (Wang 2005;Construction and Planning… 2009). Besides the basic construction, government begins to focus on improving the quality of life. Due to the international skyrocketing price and the bubble economy, caused the price of land and worker rapidly go up. This will also cause a lot of project progress to lag behind. For example, from Tables 1 and 2 can calculated that the average total building construction cost per year in  Taiwan is about 9,157,800,000 NT dollars (277,509,091 US dollars). Such construction investment is fully relative with nation's economy situation.

Development of knowledge management and applications in construction industries
In this 21st century, information technology (IT) is an important issue for economic growth of each country. The professional knowledge of IT and construction is a key factor to develop construction industry. Without such knowledge for sharing among construction project practitioners, construction management techniques may not be appropriately applied to future projects. In each country, most construction projects are built for every citizen's use. The quality of such construction projects will directly influence all users once these projects were finished. Meanwhile, if the performance of construction management doesn't work well, it not only makes worse quality but also threatens each citizen's life. Construction projects contain many different aspects such as economy, society, culture and education, medical treatment, and so on. During the whole life cycle with each construction project, life cycle includes conceptual phase, designing phase, bidding phase, construction phase and maintenance phase (Lin et al. 2005), there are lot of professional knowledge need to be supplied from every engineer. That means knowledge sharing between construction companies and employers is an important competition factor in construction industry. There are several famous businesses with their knowledge management and sharing systems. One of them is Braodvision Co. Braodvision is established in 1993 and is famous as renowned electronic commerce software supplier by the personal platform and one to one platform in worldwide, so as to assistance enterprise promotes the competitive ability and the ability to make a profit. Its customers include financial, retail sales, high tech manufacture and international telecommunication industry primarily. Braodvision's personal platform provides the formidable development tool, it's also can be used according to the customer different demand to develop the application procedure, full display the personal platform formidable function, as the knowledge management development system platform, also the highest market share knowledge management platform in U.S.A. Its software provides the enterprise toward three ways of development. Emphasized one to one personal platform service mechanism especially helps the operator establishment intimate relationship between the staff, customer and consumer. Braodvision specifically manifests the knowledge economy in two stratification planes. It already penetrates the knowledge management, causes own management to be more effective, more importantly it provides a tool. The official assistance enterprise creates the knowledge and the economy to take the initiative's product is the platform which provides the enterprise a knowledge management and penetration information share, then creation value, transforms the knowledge into the profit. Provided software product establishes the function integrity web site with the enterprise information and assistances enterprise penetrates. The personal channel can connect customer, cooperation merchant supplier and staff. For example, when general manager as soon as turns on the computer, not needs to do any search, system will automatically send the newest progress in his South Korean investment or the financial analyst forecast into his folder. This method can deliver the correct information fast to relevant staff (Chang et al. 2008;Stewart 1998;Norman 1969).
In current, there are many companies which have developed knowledge management and relative technologies. Such developments include: (1) intelligent text searching tool, (2) flexible organization for personnel management (department/group/personal authorized control environment), (3) process control tool, (4) personal message management system, (5) data analyzing tool, (6) directorybased data management system, (7) automatic reminding management system, (8) online educational management system, (9) network multimedia development system, (10) enterprise information portal system. Moreover, there are some researches on the adoption of knowledge management system (Norman 1969).
In Taiwan  Knowledge sharing and decision acquisition are problems solving expertise from knowledge sources such as human experts, texts, data and documents to another human or computer program (Buchanan et al. 1983).
People are interested in acquiring knowledge because: (1) it may help solve major problems of today and future with technological solutions; and (2) it may satisfy certain needs by filling the gap between what is at present, and what will be tomorrow (Modesitt 1992).  The knowledge management system completed by combining the development for the system framework with the suitable editing software usually includes planning for the client-server model and making a study of the demand for knowledge databases. The purpose of this research  4.1. The concept for the client-server model Centralized processing is applied to the operation in traditional mainframe: all the works were processed by the mainframe itself; the user only needs to use the keyboard to control the mainframe and the data transmitted is received and displayed by the terminal. However, when the amount of data and users increases, even with the super computer, a single mainframe is not capable of processing all the works. As the price of personal computer drops and becomes more and more powerful; the networking technology and the distributed data base management fulfills the possibility to process part of the works with the personal computer to form the client-server model (Lin and Shi 2004). Under this model, personal computers can share some of the processing works from the mainframe; it can-not break apart from the centralized processing model so the workstation gradually replaces the mainframe since the price for the mainframe is too expensive.
The functions of the World-Wide Web (WWW), Web Browser and other software (Java from Sun and ActiveX from Microsoft) are becoming more powerful. This makes the application software developing to the Multi-Tier Architecture as shown in Fig. 9. It includes client, web server and database server (Lin and Shi 2004).

System demonstration
The basic structure of this program is shown in Fig. 10. It develops a program with scientific process as mentioned above and consults more than six senior engineers to get feedback information for revising the prototype program. Finally, the contents of this prototype program include: (1) front page, (2) bulletin board, (3) revised announce, (4) discussion area, (5) knowledge sharing area and (6) knowledge mining. Fig. 11 shows several different contents of the program demonstration screens. protocol (http) and connects data base by using Open Database Connectivity (ODBC). Fig. 12 shows several program codes of this prototype system.

Analysis and development of performance evaluation model
It is also an important issue for keeping knowledge system in well condition to guarantee its performance. To develop an appropriate evaluation algorithm, this research uses analysis tools of Delphi, Analytic Hierarchy Process (AHP) and fuzzy theory with questionnaires to build up the model of assessing factors and to establish the evaluation weight. For practical application this research also uses computing technology to build up an analysis system for decision strategy.

Assessment structure calculation and development
There are three steps to build the original assessment model: (1) identifying of the assessment factors, (2) identifying of the relationship of assessment factors and (3) identifying of the grade of assessment factors. The model can be built as follows: 1. Identifying the assessment factors: according to literature and some experts' opinion, selecting fit factors were used to assess the system performance; 2. Identifying the weighting of key performance index (KPI): This part uses Analytic Hierarchy Process (AHP) to find out the weight of each factor. The analysis process of AHP is described as follows (Satty 1980;Ossadnik and Lange 1999;Timothy 2000): (1) Building up comparison matrix. In order to compare each assessment factor, it must use nominal scale as a matrix to calculate. If a specific index contains n factors to analysis, it will have n×(n-1)/2 pairs to compare. (1) (2) Calculating weighting. The calculating method is shown in Eq. (2).
where: GM i is the geometric mean of one row in compare matrix; i -row number; j -column number; a ij -factor i compared with factor j.
3. Establishing the level of KPI. Each assessment factor has its different cognition, so it must be identified with every situation for each factor. This research uses fuzzy theory to statistics the cognition of citizens from these assessment factors. The membership value calculated from questionnaire to derive three grades of its membership function within each assessment factor.

Development of the evaluation model
There are two major steps to build the performance evaluation model of knowledge management following with the original assessment model in this research. The first step is choosing evaluation factors and the second step is evaluating index of every factor. The performance evaluation model, which was built from this research, is depending on a cycling structure of knowledge management; such evaluation model is fully focusing on the core value of constructional knowledge sharing and according to the references about performance evaluation (Lin and Shi 2004;Kaplan and Norton 1996;Zadeh 1965;Csutora and Buckley 2001). This model contains design of performance evaluation factors, estimation of performance evaluating structure, algorithm of evaluating process and discussion and improvement of performance evaluation. Scientific analysis including fuzzy Delphi method, Fuzzy Analytic Hierarchy Process (FAHP) and fuzzy theory are used to build and calculate the performance result.
This evaluation model includes four levels: (1) Knowledge creation, including educational training, construction plan of knowledge management, innovative and creative staff, support for knowledge management from executive and information technology; (2) Knowledge transportation, including experiences sharing, selection mechanism of knowledge management files, professional construction technology and knowledge management and the reward system; (3) Knowledge diffusion, including knowledge sharing rate, system utility rate, working attitude, and form a group of specialists; (4) Knowledge accumulation, including knowledge database for construction engineer, follow-up services after construction, and place importance to intellectual property rights.
The total involves sixteen indexes within this evaluation model (Fig. 13). The calculating procedures of each weighting factor are briefly described below. Fig. 13. Performance evaluation model 5.3. Deriving procedure of weighting factor The calculation method for the principle weighting of this study was based on the analytic hierarchy process and used the concept of the triangular fuzzy number to gather and calculate all the valid data from the second stage of expert questionnaires.
In order to get the construction knowledge management performance evaluation to be symbolically standard, this study used the fuzzy Delphi method for the finding indexes and then used the analytic hierarchy process to calculate the weighting of the 16 indexes. 15 copies of the expert questionnaires were sent out and withdrew 12 copies. The number of valid questionnaires was 12 copies.
After obtaining the decision group opinions from the expert questionnaires, this study used the multi-decision software, Expert Choice, to calculate the relative weightings for the indexes. For example, in the evaluation aspect of knowledge creation, the calculating results of the minimum weighting factor (L min ) is 0.048, the maximum weighting factor (U max ) is 0.516 and the average weighting factor (M) is 0.139 (Fig. 14). In order to ensure the validity of each expert questionnaire, the consistency index (CI) for each questionnaire must not be greater than 0.1. Tables 3 and 4 show the calculation results.

Illustration of performance evaluation
For the practical application of the construction knowledge management performance evaluation system the case study on a domestic engineering consulting company A was performed (for the confidentiality, the company is named A company). In order to obtain the objective evaluation value of the A engineering consulting company, therefore the evaluation was performed on 3 different groups: 1 system developer, 1 senior director and 13 system users. The evaluation procedure was followed as depicted in Fig. 15. In this study the evaluation value of different indexes was compared and analyzed in order to understand the satisfaction of the system constructor, decision layer and system users. This research used the arithmetic average from the performance value to make the contribution identical. Table 5 shows the overall average performance value for each index. Fig. 16 depicts the detail results obtained from different evaluators.
From the sorting, the highest performance value is the knowledge creation, the knowledge accumulation is  Table 5 is the knowledge database for construction engineer, support for knowledge management from executive is next and educational training is the lowest. The biggest difference of the value is only 0.082. Also Fig. 16 clearly shows the difference of the performance value between different groups and the distribution chart allows coming to some conclusions: 1. Basically, the acknowledgement and the knowledge management performance index for different evaluator are similar. 2. The average performance value of the system user is lower than the others. Therefore there is big difference of understanding between the system user, system constructor and decision manager.
3. The performance value of the education training for the system user is low. This study infers that the evaluators might all be senior staff, so the education training for them was not performed by the system. 4. The performance value of the knowledge database for construction engineer is high. This is because the company's knowledge management system uses the technique document management system. The weighting of the knowledge database for construction engineer is much higher than the others so that the evaluation result is high. 5. The difference value between the highest performance value and the overall performance average value indicates there is still improvement for each index. The bigger the difference is, the more improvement it is needed. From Table 6, the difference between the highest and the average value of the knowledge management and the reward system is 0.027, which is the biggest difference of the 16 evaluation indexes so that it is the first priority needed to be improved.  6. The evaluation of the educational training, conduction plan of knowledge management, support for knowledge management from executive, information technology, professional construction technology, working attitude and forming a group of specialists is mostly the same.
7. The evaluation result of the knowledge management performance of the 13 evaluators is shown in Table 7. 3 evaluations were "excellent", 3 -"very good", 7 -"good" and 1 -"normal". In general, the overall performance value is good.

Conclusions and suggestions
This research illustrates how to build a knowledge management system for construction companies, and shows how to develop the performance evaluation model and calculate the evaluation result. From the evaluation model's result by comparing the difference between current data and the highest performance data, also with the sequence of current index, company managers could know which part will be the priority criteria to improve the business of their construction company. By the algorithm of this study the competition capability of such construction company could be increased. Then after developing and testing, the proof of knowledge management could support construction industry, organization decision ability. Competitiveness in construction industry could be promoted through this system in order to achieve the objectives of knowledge economy.
In the future, this prototype program could be used in practice to illustrate the performance evaluation. The obtained feedback could be used to improve the knowledge sharing in management of construction.