Assessment of Construction Competitiveness through Knowledge Management Process Implementation
Abstract
:1. Introduction
- To examine key KMP factors affecting the CC in construction companies.
- To explore interrelationships between key KMP factors and CC.
- To develop a self-assessment form of KMP implementation for construction companies to assess their current KM implementation and suggest plans to improve KMP and enhance CC in the long term.
2. Literature Review
2.1. KMP Factors in the Construction Industry
2.1.1. Knowledge Acquisition Factor
- The acquisition of knowledge from clients (KA1) item: Yusof and Bakar [47] mentioned that knowledge can be acquired from clients through their feedback on services. ElFar et al. [32] stated that construction companies can acquire knowledge from customer relations to catch their needs and intentions.
- The acquisition of knowledge from competitors (KA2) item: Alrubaiee et al. [40] mentioned that construction companies could acquire knowledge from competitors through their strategies and processes. Valdez-Juárez et al. [33] added that companies should acquire knowledge from competitors to update their business strategies.
- The acquisition of knowledge through the employee’s KPI processes (KA3) item: Liao and Wu [48] mentioned that the acquisition knowledge process affected employees through activities (i.e., identifying best practices, exchanging experiences, and competing performance between individuals). Bing Chong et al. [49] mentioned that knowledge could be extracted from workers through mapping knowledge.
- The acquisition of knowledge through the financial reporting systems (KA4) item: Ahmad and An [39] mentioned that data (e.g., financial data, cost, and profit) may be used to improve the body of knowledge in companies. Akram et al. [50] stated that a good KA should have a financial reporting system that is well-developed to manage financial activities and support managers in decision-making.
- The acquisition of knowledge through market research (KA5) item: Parker [51] mentioned that construction companies could extend their knowledge through markets. Jayasingam et al. [46] stated that practices associated with the acquisition of ideas and solutions could come from real market needs. Abu Bakar et al. [31] mentioned that acquisition refers to activities conducted to obtain knowledge from the business environment.
- The acquisition of knowledge through previous project experiences (KA6) item: Gonzalez and Martins [29] stated that previous experiences should be acquired to update and improve project performance. Kale and Karaman [52] mentioned that companies can acquire knowledge from defects, design changes, and planning to improve subsequent projects.
2.1.2. Knowledge Dissemination Factor
- The dissemination of hard copies to stakeholders (KD1) item: Mohamad and Mat Zin [2] mentioned that disseminating knowledge to stakeholders through hard copies (e.g., reports, newsletters, policy, and procedure manuals) improves competitiveness in construction companies. Chen and Fong [13] added that disseminating hard copies to stakeholders helps update project information and improve knowledge in construction companies.
- The dissemination of knowledge through staff mentoring (KD2) item: Chen and Fong [37] mentioned that staff mentoring could disseminate knowledge among members to maintain interactive themes for KD in companies. Ulhaq et al. [56] stated that transferring the captured knowledge to employees through mentoring and coaching can support the individual’s decision-making.
- The dissemination of knowledge of products and processes within the company using updated technology (KD3) item: Almomani et al. [35] mentioned that knowledge of products and processes disseminated using the technology will enhance the marketing innovation of companies. Allameh and Abbas [57] recommended that companies should use technology to disseminate business process knowledge to improve innovation and performance.
- The dissemination of market trends and developments among internal departments (KD4) item: Hassan and Raziq [30] mentioned that market information should be freely disseminated in companies. Lo et al. [58] added that disseminating market trends to all employees improves KD, leading to improved organizational effectiveness.
- The dissemination of knowledge by encouraging two-way communication (KD5) item: Jayasingam et al. [46] mentioned that knowledge is disseminated among people throughout the organization through meetings between departments, managers, and employees. Wibowo et al. [43] mentioned that KD should be performed to ensure that the organizational knowledge is received by all members.
2.1.3. Knowledge Responsiveness Factor
- The response to changes in client needs (KR1) item: Saini et al. [12] mentioned that responsiveness to client demand improves agility, which is the ability to adapt to continual changes in companies. Wibowo et al. [43] stated that the KR involves activities carried out as a response to clients to improve the success of projects.
- The response to the client’s reactions to technological changes (KR2) item: Akram et al. [50] stated that responding to technological changes helps companies take the best ideas from disparate functions. Yousaf and Ali [34] stated that the ability to respond to technological changes on clients improves operational effectiveness.
- The response to competitor strategies (KR3) item: Hassan and Raziq [30] mentioned that the competitors’ strategies reflect the current state of the market. Darroch [38] added that responding to competitor strategies helps firms gain more information about market trends and update their strategies proactively and effectively.
- The response to employee needs (KR4) item: Wibowo et al. [43] mentioned that responding to employees’ needs helps the company make adjustments in management. This also motivates employees to participate in KM activities.
- The response to market changes in the market plan (KR5) item: Dang et al. [4] mentioned that the model of KM capability (i.e., infrastructure and process) that responds to market changes is crucial to improving market performance. Mohamad and Mat Zin [2] stated that reacting to changes in the market helps companies improve innovation in products and processes.
2.1.4. Knowledge Storage Factor
- The authorization of accessible permission into the database (KS1) item: Albooyeh and Yaghmaie [24] mentioned that the successful implementation of a data storage system requires user participation through the use and updating of new knowledge. Allowing employees to access data at the appropriate level of responsibility is essential for the implementation of KS.
- The data screening before saving them into the database (KS2) item: Alrubaiee et al. [40] mentioned that data screening is a necessary step to ensure the reliability of data. It is a critical step in providing reliable analysis results for managers when making decisions. Tennakoon et al. [59] stated that construction project activities are driven by knowledge, and this knowledge can be stored in databases called knowledge management systems once subject experts have validated it.
- The storage of knowledge using the data warehousing technology (KS3) item: Novák [41] mentioned that the use of data storage technology is an essential part of KM. Suresh et al. [44] stated that centralized data storage provides connectivity in information management. This helps improve project management and reduce project costs.
- The storage of knowledge in hard copies (KS4) item: Fong and Choi [21] mentioned that storing data in hard copy (i.e., reports, newsletters, policy, and procedure manuals) is a traditional method in the construction industry. It is widely used in the management of construction sites in the form of drawings, acceptance records, and progress reports. Shahzad et al. [60] mentioned that hard copy, an explicit type of knowledge, requires amplification mechanisms such as procedures, IT systems, and cultural work to maximize the benefits of the combination stage of the KM process.
- The storage of lessons learned in a database (KS5) item: Park et al. [61] mentioned that the knowledge of employees needs to be stored in a knowledge storage system so that it can be easily queried and analyzed to support decision-making.
- The procedures for knowledge storage (KS6) item: Wang and Meng [14] mentioned that to collect data effectively, construction companies need to establish data collection procedures and disseminate them to all departments. This helps improve the consistency and efficiency of data collection and storage.
2.1.5. Knowledge Utilization Factor
- The use of existing knowledge to improve company business processes (KU1) item: Mohamad and Mat Zin [2] mentioned that construction companies can use the knowledge gained from their operations to improve business processes by reusing experiences from similar projects. This depends on the level of knowledge that the company possesses and the level of KM maturity.
- The use of knowledge to deal with competitive conditions (KU2) item: ElFar et al. [32] commented that knowledge is used to deal with changes in the business environment. It helps companies adapt to a dynamic market (i.e., new materials and new technologies). Egbu [62] mentioned that KM is a critical enabler for innovation to deal with competitive conditions.
- The use of knowledge to adapt strategic directions (KU3) item: Dang et al. [7] mentioned that the development of construction companies is affected by their ability to adapt to the market. The use of knowledge to build plans and strategies to create appropriate products and services will help businesses increase the efficiency of market development.
- The use of accumulated knowledge to solve problems (KU4) item: Garcia and Mollaoglu [18] mentioned that the knowledge used by individuals to solve problems reflects their ability to apply knowledge. Chen and Fong [13] stated that the knowledge accumulated by employees increases their problem-solving ability, leading to improved efficiency of the companies.
- The use of new knowledge to improve company business processes (KU5) item: Wibowo et al. [43] mentioned that the use of knowledge will create new knowledge to improve the company’s performance. It also increases the innovation of the business through the creation of improvements (i.e., using information systems for estimating and quoting instead of using experience).
2.2. Construction Competitiveness in the Construction Industry
2.3. Conceptual Model of KMP and CC Factors
- H1: Knowledge storage positively affects knowledge acquisition. Gonzalez and Martins [29] mentioned that the data warehousing of previous projects could create the appropriate conditions for organizational learning that help companies enhance knowledge acquisition from their information stored. Novák [41] stated that acquired knowledge can be maintained and transferred to other explicit things such as written documents, electronic databases, codified human knowledge, and documented organizational procedures and processes. The transformation of knowledge type between explicit and tacit knowledge creates new knowledge that extends and updates existing knowledge in companies [81].
- H2: Knowledge storage positively affects the knowledge dissemination. Al-Qubaisi et al. [36] mentioned that adopting IT in distributing knowledge could help companies increase the effectiveness of knowledge dissemination. Wang and Meng [14] mentioned that stored information tools (e.g., building information modeling) can provide a convenient way to manage information across different project phases, enable knowledge exchange between departments, and define relationships between current and previous construction activities to integrate relevant knowledge. Singh and Mirzaeifar [82] proposed a framework based on memory systems to assess the transactions of distributed content knowledge resources in modern construction projects. This helps increase the effectiveness of knowledge dissemination for project management.
- H3: Knowledge acquisition positively affects the knowledge dissemination. Chen and Fong [13] mentioned that the new knowledge acquired should be disseminated to all departments to adapt to new ideas and situations. Lessons learned from previous projects and clients can be shared through effective communication among team members to retain new knowledge and enhance work practices [34]. Teerajetgul et al. [83] mentioned that knowledge acquisition and sharing by employees consist of work trust, collaboration, and individual competency influencing onsite construction works. New knowledge acquired from markets and projects is also distributed through updated processes, guidelines, and manuals, resulting in increasing intensive activities of knowledge dissemination [13,38].
- H4: Knowledge responsiveness positively affects knowledge acquisition. Yousaf and Ali [34] mentioned that acquiring quality and quantity of information from clients is assisted by achieving effective responses to clients. To deal with new changes in the market, knowledge acquisition activities get knowledge from the market that updates and extends the existing knowledge [37]. The higher the intensity of the knowledge responsiveness, the higher the interaction with the knowledge source, and the higher the intensity of knowledge acquisition [13].
- H5: Knowledge dissemination positively affects knowledge utilization. Alashwal et al. [84] mentioned that distributing knowledge to stakeholders increases coordination and effective decision-making when dealing with project changes. Sharing knowledge among members of the project team increases the effectiveness of using knowledge to reduce mistakes and improve productivity [85,86]. The higher the intensity of knowledge dissemination, the more activities using knowledge [13].
- H6: Knowledge utilization positively affects knowledge responsiveness. Mohamad and Mat Zin [2] mentioned that data should be used and analyzed before responding to clients and competitors to demonstrate how companies transform their data and knowledge into projects and business practices. Using knowledge in production and business activities creates new knowledge, which can be used to respond to market changes [37]. Therefore, use knowledge as a trigger to increase interaction with the market by responding to changes in customers and competitors [16].
- H7: Construction competitiveness positively affects knowledge storage. Novák [41] mentioned that organizational databases and expert experiences influence organizational performance in financial, innovational, growth, and operation performance. Tennakoon et al. [59] mentioned that information on projects is stored in the systems (e.g., BIM), which helps companies manage all phases of projects effectively, resulting in a satisfaction increase in owners and stakeholders. To improve the project’s success, the information demand of management increases to tackle the risks and the changes in projects [87]. The growing market share when companies get more competitive requires more information and data for marketing activities [88]. These information demands of companies lead to a higher intensity of knowledge storage.
- H8: Construction competitiveness positively affects knowledge acquisition. Jayasingam et al. [46] stated that KA significantly affects strategic and process improvement by acquiring market, client, and employee ideas and solutions. Pietersen [89] mentioned that performance outcomes represent new knowledge that reveals the competitive position of the company, resulting in the intensity of knowledge acquisition. The demand for the management of data and information is higher when construction competitiveness increases, resulting in a higher intensity of activities of knowledge acquisition [29].
- H9: Knowledge dissemination positively affects construction competitiveness. Ren et al. [8] stated that strategies, including standardizing project management, using information and post-project evaluation systems, and encouraging a shared culture to enhance inter-project communication and transfer intention, provide superior advantages for construction companies. Arif et al. [90] mentioned that sharing knowledge improves the productivity of construction projects and affects the strategy and operation of companies. Teerajetgul and Chareonngam [91] mentioned that tacit knowledge is disseminated and re-combined based on networks among individuals in projects, facilitating a steady evolution of best practices. The higher the intensity of knowledge dissemination, the higher the construction competitiveness.
- H10: Knowledge responsiveness positively affects construction competitiveness. KR enhances the interaction between the company and its client to update information, adapt work practices following client comments, and enhance work innovation [38]. Hassan and Raziq [30] stated that knowledge responsiveness helps companies be proactive to changes and more innovative when they interact with clients and competitors. Butnariu and Luca [92] mentioned that the development of trust-based relationships depends on relational marketing with stakeholders in order to bring added value to the involved parties of projects. The higher the intensity of the knowledge responsiveness, the more construction competitiveness.
- H11: Knowledge utilization positively affects construction competitiveness. Chen and Fong [13] mentioned that effective use of knowledge may enhance business performance in terms of finance, client, process, and learning and growth [13]. Construction companies could use experiences and knowledge from previous projects to enhance performance [84]. Using KM could also help construction project managers control cost-effectively, resulting in construction competitiveness [44]. The higher the intensity of knowledge utilization the more CC improvement.
3. Research Methodology
3.1. Research Framework
3.2. Questionnaire Survey Development and Pilot Test
3.3. The Exploratory Factor Analysis and the Reliability Test
3.4. The Structural Equation Modeling Approach
4. Analyses Results
4.1. Data Collection and Data Screening Results
4.2. EFA Results
4.3. SEM Results
4.3.1. Measurement Model Results
4.3.2. Structural Model Results
5. Discussion of Results
6. Self-Assessment Form of CC through KMP Implementation
- 1—No KMP in place: KMP activities are performed randomly, and CC is achieved without KMP implementation.
- 2—Beginner level: KMP activities are recognized but not performed regularly. No standard practices are conducted.
- 3—Medium level: KMP activities are performed under a standard process. The KMP practices are assessed on a regular basis.
- 4—High level: KMP activities are acknowledged as a tool to enhance the CC and are well-managed with supporting tools.
- 5—Excellent level: KMP activities are comprehensively and continuously improved and performed in an optimized manner. A long-term KMP improvement plan is established, implemented, and regularly updated to enhance CC.
- Step 1: Each item of KMP and CC factors is assessed using a 5-point scale. The assessment score of each item is multiplied by its importance weight, and all items’ scores are summed to achieve the total score of each KMP and CC factor, (see Table 7). Please note that the assessment scores used in Table 11 are the assumed scores and do not reflect the actual status of the Vietnamese construction industry. They are used as examples for the calculation steps only. The total score of the KS factor (KSs) is (0.79 × 3) + (0.79 × 3) + (0.77 × 3) + (0.74 × 4) + (0.71 × 4) + (0.52 × 2) = 13.89 points (see Table 11). The total score is then adjusted to a maximum adjusted score of 5 points. For example, the maximum total score of the KS factor is (0.79 + 0.79 + 0.77 + 0.74 + 0.71 + 0.52) × 5 = 21.6 points when all six KS items receive 5 points in the assessment. The adjusted score of the KS factor (KSa) is then 13.89 × 5/21.6 = 3.22 points (see Table 11).
- Step 2: The influences the five KMP factors have on CC are reflected by the influential score of KMP factors on CC (KMPf). It is calculated by multiplying the adjusted scores of five KMP factors by their influential weights (see Table 10). It is summed to achieve a maximum influential score of 8.55 points (i.e., when five KMP factors receive the adjusted scores of 5 points). For example, the total effect the KS factor has on CC is 0.16 (see Table 10); this results in the influential score of the KS factor on CC of 0.16 × 3.22 = 0.52 (when the adjusted score of the KS factor is 3.22), see Table 11.
- Step 3: The final score of CC through KMP implementation (CCKMP) is finally calculated by summing the adjusted score of CC (CCa) with the influential score of KMP factors on CC (KMPf). It is then adjusted to a maximum score of 5 points by multiplying by 5 and dividing by 13.55 (which is the maximum score of CCa and KMPf, i.e., 5 + 8.55 = 13.55 points). In Table 11, the CCKMP is (3.28 + 5.09) × 5/13.55 = 3.09.
7. Implications for the Construction Industry
- In the short term, project managers may organize a weekly meeting on sites to discuss problems and challenges with workers. Workers with good examples are invited to give a short talk on their performance, and their stories are posted on the company website. Social communication channels are encouraged to promptly manage and solve problems on sites. The new technology as building information modeling (BIM) and 3D model, is utilized in client discussions, and the discussion summaries are recorded for future reference.
- In the long term, the company should invest in data warehousing to effectively record, analyze, and use the data to minimize possible human errors. Skill training in data warehousing is required for effective utilization. The BIM is encouraged to be used to closely monitor the work progress, manage problems, and record solutions for future uses.
8. Conclusions and Recommendations
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
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Construct | Item | Description | Reference |
---|---|---|---|
KA | KA1 | Acquiring knowledge from clients | [21,29,31,32,33,34] |
KA2 | Acquiring knowledge from competitors | ||
KA3 | Acquiring knowledge through the employee’s KPI processes | ||
KA4 | Acquiring knowledge through financial reporting systems | ||
KA5 | Acquiring knowledge through market research | ||
KA6 | Acquiring knowledge through previous project experiences | ||
KA7 | Acquiring knowledge from the standard benchmarking systems | ||
KD | KD1 | Disseminating hard copies (e.g., reports, newsletters, policy, and procedure manuals) to stakeholders | [2,13,30,34,35,36] |
KD2 | Disseminating knowledge through staff mentoring | ||
KD3 | Disseminating knowledge of products and processes within the company using updated technology | ||
KD4 | Disseminating market trends and developments among internal departments | ||
KD5 | Disseminating knowledge using encouraging two-way communication | ||
KR | KR1 | Responding positively to changes in client needs | [2,4,30,34,37,38] |
KR2 | Responding to the client’s reactions to technological changes | ||
KR3 | Responding to competitor strategies | ||
KR4 | Responding to employee needs | ||
KR5 | Responding to market changes in the market plan | ||
KS | KS1 | Authorizing the accessible permission into the database | [14,21,24,39,40,41] |
KS2 | Conducting data screening before saving them into the database | ||
KS3 | Storing knowledge using the data warehousing technology | ||
KS4 | Storing knowledge in hard copies (e.g., reports, newsletters, policy, and procedure manuals) | ||
KS5 | Storing lessons learned into the database (knowledge storage system) | ||
KS6 | Having procedures for knowledge storage | ||
KU | KU1 | Using existing knowledge to improve company business processes | [2,13,42,43] |
KU2 | Using knowledge to deal with competitive conditions | ||
KU3 | Using knowledge to adapt strategic directions | ||
KU4 | Using accumulated knowledge to solve problems | ||
KU5 | Using new knowledge to improve company business processes |
Reference | Profit (PF) | Client Satisfaction (CS) | Labor Productivity (LP) | Innovative Work Process (IN) | Timely Project Completion (TM) | Project Quality (QL) |
---|---|---|---|---|---|---|
Abu Bakar et al. [31] | x | x | ||||
Alrubaiee et al. [40] | x | x | ||||
Chan [72] | x | x | x | x | x | x |
Chen and Fong [13] | x | x | x | x | x | |
Chen and Fong [37] | x | x | x | x | x | |
Chen and Huang [73] | x | |||||
Chen and Liang [68] | x | x | x | |||
Chen and Mohamed [3] | x | x | x | x | x | |
Cheung and Qi [74] | x | |||||
Dang et al. [4] | x | |||||
Dang et al. [7] | x | |||||
Darroch [38] | x | x | ||||
Darroch and McNaughton [75] | x | x | ||||
Deng and Smyth [76] | x | x | x | x | x | |
Duodu and Rowlinson [69] | x | x | x | x | ||
ElFar et al. [32] | x | x | x | |||
Enshassi et al. [77] | x | x | x | x | x | x |
Fong and Chen [42] | x | x | x | x | x | |
Gholami et al. [67] | x | x | ||||
Gold et al. [28] | x | |||||
Graham and Thomas [78] | x | x | ||||
Gunasekera and Chong [25] | x | x | x | |||
Hassan and Raziq [30] | x | |||||
Hussinki et al. [66] | x | x | ||||
Jayasingam et al. [46] | x | |||||
Mohamad and Mat Zin [2] | x | x | ||||
Soewin and Chinda [64] | x | x | x | x | x | x |
Sweis et al. [79] | x | x | x | |||
Yousaf and Ali [34] | x |
Information | Percentage |
---|---|
Experience | |
Up to 5 years | 29.8 |
6–10 years | 30.9 |
11–15 years | 30.1 |
>15 years | 9.2 |
Position | |
Project engineer | 27.2 |
Project manager | 19.1 |
Officer | 18.8 |
Team leader/Site manager | 14.7 |
Division manager | 10.7 |
Others | 9.5 |
Job title | |
Project & construction management | 34.9 |
Technical supervision/construction | 21.7 |
Management/administration | 13.6 |
Structural design | 11.0 |
Planning | 4.0 |
Others | 14.8 |
Type of company | |
Private company | 73.2 |
Public Company | 17.3 |
Foreign direct investment | 9.5 |
Number of employees | |
<100 employees | 31.7 |
100–199 employees | 27.9 |
≥200 employees | 40.4 |
Item | Mean | Standard Deviation |
---|---|---|
KA1 | 3.95 | 0.79 |
KA2 | 4.05 | 0.86 |
KA3 | 3.86 | 0.84 |
KA4 | 3.75 | 0.83 |
KA5 | 4.03 | 0.84 |
KA6 | 4.31 | 0.77 |
KA7 | 3.97 | 0.86 |
KD1 | 3.60 | 0.93 |
KD2 | 3.97 | 0.83 |
KD3 | 4.13 | 0.82 |
KD4 | 3.99 | 0.73 |
KD5 | 4.14 | 0.73 |
KR1 | 4.22 | 0.78 |
KR2 | 4.01 | 0.80 |
KR3 | 3.74 | 0.91 |
KR4 | 3.90 | 0.90 |
KR5 | 4.16 | 0.79 |
KS1 | 3.79 | 0.87 |
KS2 | 3.93 | 0.80 |
KS3 | 3.93 | 0.89 |
KS4 | 3.37 | 1.03 |
KS5 | 3.98 | 0.76 |
KS6 | 3.98 | 0.77 |
KU1 | 3.91 | 0.83 |
KU2 | 3.97 | 0.78 |
KU3 | 4.05 | 0.78 |
KU4 | 4.01 | 0.80 |
KU5 | 4.18 | 0.75 |
IN | 4.08 | 0.80 |
TM | 3.97 | 0.84 |
CS | 4.01 | 0.75 |
QL | 4.07 | 0.78 |
ES | 3.91 | 0.81 |
LP | 4.03 | 0.75 |
PF | 3.94 | 0.87 |
Item | Factor Extracted | α Value | |||||
---|---|---|---|---|---|---|---|
KA | KD | KR | KS | KU | CC | ||
KA4 | 0.643 | 0.852 | |||||
KD1 | 0.596 | ||||||
KA3 | 0.393 | ||||||
KA5 | 0.378 | ||||||
KA7 | 0.324 | ||||||
KA2 | 0.303 | ||||||
KA1 | 0.302 | ||||||
KD5 | 0.521 | 0.798 | |||||
KD2 | 0.387 | ||||||
KD3 | 0.367 | ||||||
KD4 | 0.318 | ||||||
KR5 | 0.747 | 0.812 | |||||
KR1 | 0.684 | ||||||
KR2 | 0.565 | ||||||
KA6 | 0.522 | ||||||
KR3 | 0.402 | ||||||
KR4 | 0.353 | ||||||
KS6 | 0.710 | 0.858 | |||||
KS2 | 0.607 | ||||||
KS1 | 0.587 | ||||||
KS5 | 0.516 | ||||||
KS3 | 0.423 | ||||||
KS4 | 0.315 | ||||||
KU2 | 0.725 | 0.883 | |||||
KU5 | 0.703 | ||||||
KU4 | 0.688 | ||||||
KU3 | 0.659 | ||||||
KU1 | 0.649 | ||||||
IN | 0.781 | 0.887 | |||||
TM | 0.757 | ||||||
CS | 0.743 | ||||||
QL | 0.743 | ||||||
ES | 0.733 | ||||||
LP | 0.700 | ||||||
PF | 0.641 |
Variable | KA | KD | KR | KS | KU | CC |
---|---|---|---|---|---|---|
KA | 1 | |||||
KD | 0.713 ** | 1 | ||||
KR | 0.766 ** | 0.630 ** | 1 | |||
KS | 0.741 ** | 0.700 ** | 0.611 ** | 1 | ||
KU | 0.662 ** | 0.719 ** | 0.574 ** | 0.605 ** | 1 | |
CC | 0.629 ** | 0.687 ** | 0.602 ** | 0.584 ** | 0.680 ** | 1 |
Fit Index | Recommended Value | Baseline Model | Best-Fit Measurement | Best-Fit Structural |
---|---|---|---|---|
χ2/df | <3 [30] | 3.0 | 2.9 | 2.4 |
RMSEA | ≤0.08 [101] | 0.09 | 0.08 | 0.07 |
CFI | >0.8 [86] | 0.8 | 0.8 | 0.9 |
Hypothesis | Best-Fit Measurement Model Results | Best-Fit Structural Model Results | ||
---|---|---|---|---|
Correlation Coefficient | Significance | Path Coefficient | Significance | |
H1 | 0.77 | Yes | 0.45 *** | Yes |
H2 | 0.79 | Yes | 0.47 *** | Yes |
H3 | 0.68 | Yes | 0.36 ** | Yes |
H4 | 0.38 | Yes | 0.60 *** | Yes |
H5 | 0.30 | Yes | 0.74 *** | Yes |
H6 | 0.45 | Yes | 0.56 *** | Yes |
H7 | 0.36 | Yes | 0.48 *** | Yes |
H8 | 0.39 | Yes | 0.09 | No |
H9 | 0.59 | Yes | 0.01 | No |
H10 | 0.40 | Yes | 0.33 *** | Yes |
H11 | 0.59 | Yes | 0.45 *** | Yes |
KD | KU | KA | KR | |||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|
Direct | Indirect | Total | Direct | Indirect | Total | Direct | Indirect | Total | Direct | Indirect | Total | |
KS | 0.47 | (0.45 × 0.16) = 0.16 | 0.63 | - | (0.45 × 0.36 × 0.47) + (0.47 × 0.74) = 0.47 | 0.47 | 0.45 | (0.47 × 0.74 × 0.56 × 0.6) = 0.12 | 0.57 | - | (0.47 × 0.74 × 0.56) = 0.19 | 0.19 |
KD | - | - | - | 0.74 | - | 0.74 | - | (0.74 × 0.56 × 0.6) = 0.25 | 0.25 | - | (0.74 × 0.56) = 0.41 | 0.41 |
KU | - | (0.56 × 0.6 × 0.36) = 0.12 | 0.12 | - | - | - | - | (0.56 × 0.6) = 0.34 | 0.34 | 0.56 | - | 0.56 |
KA | 0.36 | - | 0.36 | - | (0.36 × 0.74) = 0.27 | 0.27 | - | - | - | - | (0.36 × 0.74 × 0.56) = 0.15 | 0.15 |
KR | - | (0.6 × 0.36) = 0.22 | 0.22 | - | (0.6 × 0.36 × 0.74) = 0.16 | 0.16 | 0.6 | - | 0.6 | - | - | - |
Factor | Direct Effect | Indirect Path | Indirect Effect | Total Effect |
---|---|---|---|---|
KU | 0.45 | KU-KR-CC | 0.56 × 0.33 = 0.18 | 0.63 |
KD | - | KD-KU-CC | 0.74 × 0.45 = 0.33 | 0.47 |
KD-KU-KR-CC | 0.74 × 0.56 × 0.33 = 0.14 | |||
KR | 0.33 | - | - | 0.33 |
KS | - | KS-KD-KU-CC | 0.47 × 0.74 × 0.45 = 0.16 | 0.16 |
KA | - | KA-KD-KU-CC | 0.36 × 0.74 × 0.45 = 0.12 | 0.12 |
Sum | 0.78 | 0.93 | 1.71 |
Factor | Items | Important Weight | Assessment Score * | Calculated Score |
---|---|---|---|---|
KS | KS2 | 0.79 | 3 | 2.37 |
KS5 | 0.79 | 3 | 2.37 | |
KS6 | 0.77 | 3 | 2.31 | |
KS1 | 0.74 | 4 | 2.96 | |
KS3 | 0.71 | 4 | 2.84 | |
KS4 | 0.52 | 2 | 1.04 | |
Total score of KS | 13.89 | |||
Adjusted score (KSa) = 13.89 × 5/21.60 = 3.22 | ||||
KA | KA5 | 0.72 | 3 | 2.16 |
KA4 | 0.69 | 3 | 2.07 | |
KA7 | 0.69 | 2 | 1.38 | |
KA3 | 0.66 | 3 | 1.98 | |
KA2 | 0.66 | 4 | 2.64 | |
KA1 | 0.66 | 3 | 1.98 | |
KD1 | 0.56 | 2 | 1.12 | |
Total score of KA (KAs) | 13.33 | |||
Adjusted score (KAa) = 13.33 × 5/23.20 = 2.87 | ||||
KD | KD4 | 0.72 | 3 | 2.16 |
KD3 | 0.70 | 2 | 1.40 | |
KD2 | 0.69 | 4 | 2.76 | |
KD5 | 0.68 | 4 | 2.72 | |
Total score of KD (KDs) | 9.04 | |||
Adjusted score (KDa) = 9.04 × 5/13.95 = 3.24 | ||||
KR | KR5 | 0.73 | 3 | 2.19 |
KR2 | 0.69 | 4 | 2.76 | |
KR1 | 0.68 | 2 | 1.36 | |
KR3 | 0.61 | 2 | 1.22 | |
KA6 | 0.60 | 3 | 1.80 | |
KR4 | 0.60 | 3 | 1.80 | |
Total score of KR (KRs) | 11.13 | |||
Adjusted score (KRa) = 11.13 × 5/19.55 = 2.85 | ||||
KU | KU5 | 0.80 | 3 | 2.40 |
KU3 | 0.77 | 3 | 2.31 | |
KU1 | 0.77 | 3 | 2.31 | |
KU2 | 0.74 | 2 | 1.48 | |
KU4 | 0.73 | 3 | 2.19 | |
Total score of KU (KUs) | 10.69 | |||
Adjusted score (KUa) = 10.69 × 5/19.05 = 2.81 | ||||
CC | IN | 0.79 | 3 | 2.37 |
CS | 0.75 | 3 | 2.25 | |
TM | 0.73 | 3 | 2.19 | |
ES | 0.72 | 3 | 2.16 | |
QL | 0.71 | 4 | 2.84 | |
LP | 0.70 | 4 | 2.80 | |
PF | 0.65 | 3 | 1.95 | |
Total score of CC (CCs) | 16.56 | |||
Adjusted score (CCa) = 16.56 × 5/25.25 = 3.28 | ||||
KMP factor | Total effect | Adjusted score | Influential score | |
The influences of KMP factors on CC | KS | 0.16 | 3.22 | 0.52 |
KA | 0.12 | 2.87 | 0.34 | |
KD | 0.47 | 3.24 | 1.52 | |
KR | 0.33 | 2.85 | 0.94 | |
KU | 0.63 | 2.81 | 1.77 | |
Influential score of KMP factors on CC (KMPf) = 0.52 + 0.34 + 1.52 + 0.94 + 1.77 = 5.09 | ||||
Final score of CC through KMP implementation (CCKMP) = (CCa + KMPf) × 5/13.55 = (3.28 + 5.09) × 5/13.55 = 3.09 |
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Khoa, V.D.; Chinda, T. Assessment of Construction Competitiveness through Knowledge Management Process Implementation. Sustainability 2023, 15, 15897. https://doi.org/10.3390/su152215897
Khoa VD, Chinda T. Assessment of Construction Competitiveness through Knowledge Management Process Implementation. Sustainability. 2023; 15(22):15897. https://doi.org/10.3390/su152215897
Chicago/Turabian StyleKhoa, Vo Dang, and Thanwadee Chinda. 2023. "Assessment of Construction Competitiveness through Knowledge Management Process Implementation" Sustainability 15, no. 22: 15897. https://doi.org/10.3390/su152215897