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題名:使用模糊MCDM模型評估知識品質
作者:戴志謙
作者(外文):Tai,Chih-Chien
校院名稱:中華大學
系所名稱:管理博士學位學程
指導教授:魏秋建
學位類別:博士
出版日期:2024
主題關鍵詞:知識管理模糊理論多準則決策方法knowledge managementfuzzy theorymulti-criteria decision making
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知識管理的目的是通過知識提案系統挖掘每個企業成員積累的隱性知識。每個知識提案都必須經過評估,通過品質評估後,知識提案將存儲在知識庫中,並與工作中需要知識的其他員工共用。從長遠來看,全體員工的能力將逐步增強,企業的競爭力自然會增強。對知識品質的正確評估是知識管理成功的關鍵。一些學者建議使用AHP(Analytic Hierarchy Process)層級分析法來確定知識的品質。這種方法的問題在於AHP只能獲得所有知識的相對品質,而不是知識的實際品質。因此,本研究提出一種模糊評估模型來衡量知識品質,該模型包括知識品質模糊指數(KQFI)和檢查通道(a checking gate)。首先,專家對標準權重和知識品質進行語意評估。然後將所有語意評估整合到知識品質模糊指數(KQFI)中,該指數與模糊閾值(FT)進行比較;然後,獲得KQFI對FT的良好程度。如果大於0.5,則表示知識提案的品質合格;否則,意味著知識提案的品質不合格。本研究使用一個包括五位專家和九個知識提案的案例來證明該方法的適用性。該方法最終判斷六個知識實例為合格,三個為不合格。結果表明所提方法確實能夠幫助企業有效篩選知識提案。
The purpose of knowledge management is to excavate the tacit knowledge accumulated by each enterprise member through the knowledge proposal system. Each knowledge proposal must be assessed, and after passing the quality assessment, the knowledge proposal will be stored in the knowledge repository and shared with other employees who need the knowledge at work. In the long run, the capabilities of all employees will gradually enhance, and the competitiveness of enterprises will naturally increase. It can be seen that the correct assessment of knowledge quality is the key to the success of knowledge management. Some scholars propose to use AHP (Analytical Hierarchical Process) to determine the quality of knowledge. The problem with this approach is that AHP can only obtain the relative quality of all knowledge, not the actual quality of knowledge. Therefore, this study proposes a fuzzy assessment model to measure knowledge quality, which includes a knowledge quality fuzziness index (KQFI) and a checking gate. First of all, experts conduct linguistic evaluation on the weight of criteria and knowledge quality. All linguistic evaluations are then integrated into a knowledge quality fuzziness index (KQFI), which is compared with a fuzzy threshold (FT), then the level of goodness of KQFI to FT is obtained. If it is greater than 0.5, it means that the quality of the knowledge proposal is qualified, otherwise, it means that the quality of the knowledge proposal is unqualified. This study uses a case including 5 experts and 9 knowledge proposals to demonstrate the applicability of the method. The results show that the method finally judges 6 knowledge as qualified and 3 knowledge as unqualified. The results show that the proposed method can indeed assist enterprises to effectively screen knowledge proposals.
王根傑(2023)。電氣自動化控制領域中人工智慧技術的應用探索。工程技術研究,5(3),58-60。
何志青(2018)。知識論的轉折,(Vol. 13),國立臺灣大學出版中心。
呂雅芳、張瑞益(2023)。結合LSTM 股價預測與基因模糊交易策略—以台灣50為例 (Doctoral dissertation)。台灣大學工程科學及海洋工程學系碩士論文,臺北市。
李允中、王小璠、蘇木春(2003)。模糊理論及其應用,全華科技圖書股份有限公司,臺北市。
李佳瑉、王一帆、黃洪運、李梓珂、蔡幽娜、嚴欣怡(2023)。基於CRCS的空管安全風險指數評估。中國民航大學,空中交通管理學院,天津Open Journal of Transportation Technologies,12,364。
周燕、錢慧池、王楠。隱性知識共用對知識型員工越軌創新的影響機制研究—角色寬 度自我效能與工作繁榮的鏈式仲介作用。科技進步與對策,40(11),151-160。
林秀芬、李國光、褚麗絹。知識分享影響因素評估模式建構之研究。管理與資訊學報 11,2006,195-224。
林信成、彭啟峰(1994)。Oh! Fuzzy, 模糊理論剖析,第三波文化事業股份有限公司。
邱琳(2023)。我國基於AHP-Fuzzy模糊綜合評判的以房養老風險評估。Operations Research and Fuzziology,13,2241。
胡丁集、胡長德、王起、顧怡紅(2023)。基於立體視覺的機器人自主乘梯控制方法設計與研究。Mechanical Engineering and Technology,12,76。
栗曉宇、杜嶽峰、劉磊、毛恩榮(2023)。玉米低損籽粒直收機自動控制系統設計與試驗。中國農業工程學會學報。2023年,卷。39第2期,第34-42頁。.
郝琳、張亞超(2021)。電氣自動化控制中人工智慧技術的應用。輕工科技,37(06),59-60。
張基成、蔡政緯(2012)。以網路模糊德懷術與模糊層級分析法發展數位化學習歷程檔案之知識管理行為量表。教育資料與圖書館學,50(1),103-133。
郭凱紅、王紫晴(2022)。Hamming-Hausdorff 距離下區間直覺模糊知識測度及應用。軟體學報,33(11),中國科學院軟體研究所4251-4267。
陳宏志。科技應用工具運用於無形文化資產登錄及認定之探討。科技博物,26(4), 5-24。
陳誠亮、王子奇、楊尚峰(2002)。模糊理論簡介及其在家電與工業上的應用。科儀新知,24: 1= 129民91.08,62-76。
趙晶(2014)。台達可編程控制器原理與應用。福建:廈門大學出版社,2014:221-221。
劉京偉(2000)。知識管理的第一本書。臺北:商周。
劉春暉、張政、張月、盧文娟、衛永琴(2022)。考慮多變路況的機器人循跡優化教學實驗。電氣電子教學學報,44(5)。
衛旭芳、劉彬(2023)。美軍數字工程建設發展研究及啟示。航空兵器,第30卷第3期,2023年7月20日。
賴榮斌(2013)。應用模糊多準則決策分析於新技術導入評估模式之研究-以台灣模具廠商為例,國立臺灣師範大學工業教育學系碩士論文,臺北市。
龍興波、劉亮亮、劉栩、葉青、朱建偉、顧建華、周威。面向醫護人員的資訊集成與應用服務平臺的設計和實踐,中國醫療設備,38(4),112-118。
龔曆菁、樂琦(2023)。基於混合模糊多指標的醫療服務匹配決策方法。Operations Research and Fuzziology,13,900。
Abdollahbeigi, B., Salehi, F. Knowledge quality and non-financial performance-A Malaysian experience. Knowledge and Process Management 2021, 29, 12-22.
Aljuwaiber, A. Communities of practice as an initiative for knowledge sharing in business organizations: a literature review. Journal of Knowledge Management 2016, 20, 731-748.
Arora, M. & Chakrabarti D. Knowledge Quality Assessment in Knowledge Management Systems. International Journal of Knowledge Management and Practices 2014, 2, 1-5.
Axtell, P. The most productive meetings have fewer than 8 people. Harvard Business Review 2018.
Azhar, N. A, Radzi, N. A., & Wan Ahmad, W. S. H. M. (2021). Multi-criteria decision making: a systematic review. Recent Advances in Electrical & Electronic Engineering (Formerly Recent Patents on Electrical & Electronic Engineering), 14(8), 779-801.
Chakrabarti, D., Arora, M., Sharma, P. Evaluating knowledge quality in knowledge management systems. Journal of Statistics Applications & Probability 2018, 7, 75-84.
Chang, P.T., Hung, K.C. Applying the fuzzy-weighted-average approach to evaluate network security systems. Computers and Mathematics with Applications 2005, 49, 1797-1814.
Chang, T. H., & Wang, T. C. (2009). Using the fuzzy multi-criteria decision-making approach for measuring the possibility of successful knowledge management. Information sciences, 179(4), 355-370.
Chen, C.T. Extensions of the TOPIS for group decision-making under fuzzy environment. Fuzzy Sets and Systems 2000, 114, 1-9.
Chen, W. & Tan, J.S.H.; Pi, Z. The spiral model of collaborative knowledge improvement: an exploratory study of a networked collaborative classroom. International. Journal of Computer Supported Collaborative Learning 2021, 16, 7-35.
Cheng, C.H. & Lin, Y. Evaluating the main battle tank using fuzzy decision theory with linguistic criteria evaluation. European Journal of Operational Research 2002, 142, 174-186.
Cheng, S.L. & Kuan, Y.W. A fuzzy logic-based knowledge management performance measurement system for SMEs. Cybernetics and Systems 2017, 48, 277-302.
Choi, H.J. & Ahn, J.C., Jung, S.H.; Kim, J.H. Communities of practice and knowledge management systems: effects on knowledge management activities and innovation performance. Knowledge Management Research & Practice 2020, 18, 53-68.
Chu, P. V, Hsu, Y. L., & Fehling, M. (1996). A decision support system for project portfolio selection. Computers in industry, 32(2), 141-149.
Clement, A.M.; Bharatraj, J. Theory of triangular fuzzy number. National Conference on Advanced Trends in Mathematics. Thiruvalluvar University, 2017.
Davenport, Thomas H. (1994), Saving IT's Soul: Human Centered Information Management. Harvard Business Review, March-April, 72 (2) pp. 119-131. Duhon, Bryant (1998), It's All in our Heads. Inform, September, 12 (8).
Dong, W.M.; Wong, F.S. Fuzzy weighted averages and implementation of the extension principle. Fuzzy Sets and Systems 1987, 21, 183-199.
E. H. Mamdani and S. Assilian, Int. J. Man-Machine Stud., 7, 1 (1975).
Efe, B. An integrated fuzzy multi criteria group decision making approach for ERP system selection. Applied Soft Computing 2016, 38, 106-117.
Emmerling, T. & Rooders, D. 7 Strategies for better group decision-making. Harvard Business Review, 2022.
Fan, Z.P. An approach to multiple attribute decision making based on fuzzy preference information on alternative. Fuzzy Sets and Systems 2002, 131, 101-106.
Ganguly, A.; Talukdar, A.; Chatterjee, D. Evaluating the role of social capital, tacit knowledge sharing, knowledge quality and reciprocity in determining innovation capability of an organization. Journal of Knowledge Management 2019, 23, 1105-1135.
Harris, T. G. (1993). The post-capitalist executive: An interview with Peter F. Drucker. Harvard business review, 71(3), 114-122.
Hashmi, N.; Shankaranarayanan, G.; Malone, T.W. Is bigger better? A study of the effect of group size on collective intelligence in online groups. Decision Support Systems 2023, 167, 113914.
Howard Raiffa, Decision Analysis. Introductory Lectures on Choices Under Uncertainty, Reading (Mass.), Addison-Wesley, 1970 2, pp. 330。
Hsu, H.M. & Chen, C.T. Aggregation of fuzzy opinions under group decision making. Fuzzy Sets and Systems 1996, 79, 279-285.
Irvine, D. S., & Huang, J. (2023). International Experience and Outcomes of OR Emergency Manual Implementation. ASA Monitor, 87(5), 35-36.
Jamwal, A.; Agrawal, R.; Sharma, M.; Kumar, V. Review on multi-criteria decision analysis in sustainable manufacturing decision making. International Journal of Sustainable Engineering 2021, 14, 202-25.
Kao, C. & Liu, S.T. Fractional programming approach to fuzzy weighted average. Fuzzy Sets and Systems 2001, 120, 435-444.
Kaushik, M.; Kumar, M. Distance and similarity-based aggregation method in intuitionistic fuzzy fault tree analysis. 2023.
Ko, A.; Vas, R.; Kovacs, T.; Szabo, I. Knowledge Creation from the perspective of the supply chain, the role of ICT. Society and Economy 2019, 41, 311-329.
Kukkurainen, P. Fuzzy logic and Zadeh algebra. Advances in Pure Mathematics 2017, 7, 350-365.
Kumar, A.; Sah, B.; Singh, A.R.; Deng, Y.; He, X.N.; Kumar, P.; Bansal, R.C. A review of multi criteria decision making (MCDM) towards sustainable renewable energy development. Renewable and Sustainable Energy Reviews 2017, 69, 596-609.
L. A. Zadeh, "Fuzzy sets," Information and Control, vol. 8, no. 3, pp. 338-353, June 1965.
L. P. Holmblod and J. J. Østergaard, Fuzzy Information and Decision Processors, M. M. Gupta and E. Sanchez eds., NorthHolland, 389 (1982).
Lee, D. H.; Park, D. An efficient algorithm for fuzzy weight average. Fuzzy Sets and Systems 1997, 87, 39-45.
Lee, H. S. (1999, October). An optimal aggregation method for fuzzy opinions of group decision. In IEEE SMC'99 Conference Proceedings. 1999 IEEE International Conference on Systems, Man, and Cybernetics (Cat. No. 99CH37028) (Vol. 3, pp. 314-319). IEEE.
Lee, H.S. Optimal consensus of fuzzy opinions under group decision making environment. Fuzzy Sets and Systems 2002, 132, 303-315.
Leonardo, M.A.; Sanín, C.; Szczerbicki, E. Quality assessment of experiential knowledge. Cybernetics and Systems 2012, 43, 96-113.
Leonardo, M.A.; Szczerbicki, E.; Sanín, C. A proposal for a knowledge market based on quantity and quality of knowledge. Cybernetics and Systems 2013, 44, 118-132.
Li, H.L.; Yang, J.Q.; Xiang, Z.Q. A fuzzy linguistic multi-criteria decision-making approach to assess emergency suppliers. Sustainability 202, 14.
Li, M., Jin, L., & Wang, J. (2014). A new MCDM method combining QFD with TOPSIS for knowledge management system selection from the user's perspective in intuitionistic fuzzy environment. Applied soft computing, 21, 28-37.
Lim, R.A.; Siew Lee, H.A.; Lim, T.M. A Study on Knowledge Quality and Job Performance of Knowledge Workers by Analyzing Content of Social Network Sites Using Sentiment Network Analysis. Inf. Manag. Bus. Rev. 2013, 5, 525-530.
Lin, C. & Hsieh, P.J. A fuzzy decision support system for strategic portfolio management. Decision Support Systems 2004, 38, 383-398.
Lin, C.; Tan, B.; Hsieh, P.J. Application of the fuzzy weighted average in strategic portfolio management. Decision Sciences 2005, 36, 489-510.
Lin, C.T. & Chen, C.T. Bid/no-bid decision-making-a fuzzy linguistic approach. International Journal of Project Management 2004, 22, 585-593.
Liu, W. & Wang, Y.; Li, L. Research on the optimal aggregation method of judgment matrices based on spatial steiner-weber point. Journal of System Science and Complexity 36, 1228-1249.
Lu, Y, Yang, Z, Eddy, D, & Krishnamurty, S. "Self-Improving Additive Manufacturing Knowledge Management." Proceedings of the ASME 2018 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. Volume 1B: 38th Computers and Information in Engineering Conference. Quebec City, Quebec, Canada. August 26-29, 2018.
Lynn, M.R. Determination and quantification of content validity. Nursing Research 1986, 35, 382-386.
Mohajan, H.K. The impact of knowledge management models for the development of organizations. Journal of Environmental Treatment Techniques 2017, 5, 12-33.
Nonaka, I. & Takeuchi, H. (1995). The Knowledge Creation Company. How Japanese Companies Create the Dynamic of Innovation. Oxford: Oxford University Press.
Nonaka, I. A dynamic theory of organizational knowledge creation. Institute of Business Research, Hitotsubashi University, Kunitachi, Tokyo, Japan, 1994, 14-3.
Novák, V. (2017, July). Fuzzy logic in natural language processing. In 2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE) (pp. 1-6). IEEE.
Pavlacka, O.; Pavlackova, M. On the properties of the fuzzy weighted average of fuzzy numbers with normalized fuzzy weights. Iranian Journal of Fuzzy Systems 2021, 18, 1-17.
Pavlacka, O.; Pavlackova, M; Hetflei, V. Fuzzy weighted average as a fuzzified aggregation operator and its properties. Kybernetika, 2017, 53, 137-160.
Peter Drucker, The New Realities-1989, From http://www.peterfdrucker. com.
Ramesh, R., & Zionts, S. (2012). Programming Package,” Foundations Control En-gineering 12 (3), 101–120.[4] Franz, LS and SM Lee (1981). “A Goal Pro-gramming Based Interactive Decision Support System,” Lecture Notes in Economics and Mathe. Encyclopedia of Operations Research and Management Science, 419.
Senge, P. M. (2006). The fifth discipline: The art and practice of the learning organization. Broadway Business.
Spaangler, S.C.; Skovira, R.J.; Kohun, F.G. Key factors in a successful knowledge management model. Online Journal of Applied Knowledge Management 2015, 3, 51-60.
Stojčić, M.; Zavadskas, E.K.; Pamučar, D.; Stević, Ž.; Mardani. A. Application of MCDM Methods in Sustainability Engineering: A Literature Review 2008-2018. Symmetry 2019, 11, 350.
Sudha, T.; Jayalalitha, G. Fuzzy triangular numbers in - Sierpinski triangle and right-angle triangle. Journal of Physics: Conference Serie.
Sveiby, K. E. (1997). The new organizational wealth: Managing & measuring knowledge-based assets. Berrett-Koehler Publishers.P48.
Tamilmani, C. Arithmetic operation of fuzzy numbers using Α-cut method. International Journal of Innovative Science, Engineering & Technology 2015, 2, 299-315.
Taylor E. We Agree, Don’t We? The Delphi method for health environments research. Health Environments Research & Design Journal 2020, 13, 11-23.
Tseng, M. L. (2011). Using a hybrid MCDM model to evaluate firm environmental knowledge management in uncertainty. Applied soft computing, 11(1), 1340-1352.
Verma, R.; Sharma, B. Intuitionistic fuzzy Einstein prioritized weighted average operators and their application to multiple attribute group decision making. Applied Mathematics & Information Sciences 2015, 9, 3095-3107.
Waheed, M., Kaur, K. Knowledge quality: A review and a revised conceptual model. Information Development 2016, 32, 271-284.
Wang, R.C., Chu, S.J. Group decision-making using a fuzzy linguistic approach for evaluating the flexibility in a manufacturing system. European Journal of Operational Research 2004, 154, 563-572.
Xiang, Y.D., Zhang, P.Z., Wu, S. Content-based knowledge quality assessment and its application in health management system. Journal of Shanghai Jiaotong University 2021, 26, 116-128.
Yoo, D.K.; Vonderembse, M. A., Ragu‐Nathan, T.S. Knowledge quality: antecedents and consequence in project teams. Journal of Knowledge Management 2011, 15, 329-343.
Zavadskas, E.K., Turskis, Z, Kildienė, S. State of art surveys of overviews on MCDM/MADM methods. Technological and Economic Development of Economy 2014, 20, 165-179.
Zhang, G., Lu, J. An integrated group decision-making method dealing with fuzzy preference for alternatives and individual judgments for selection criteria. Group Decision and Negotiation 2003, 12, 501-515.
Zhou, X., Min, M., Zhang, Z. Research on the social capital, knowledge quality and product innovation performance of knowledge-intensive firms in China. Frontier in Psychology 2022, 13:946062.


 
 
 
 
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