運用 CART 決策樹模型提供營造廠於採購 階段議價策略之研究

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姓名

李宗耿(Tsung-Keng Lee) 查詢紙本館藏

畢業系所

土木系營建管理碩士班

論文名稱

運用 CART 決策樹模型提供營造廠於採購階段議價策略之研究
(Facilitating contract negotiation in procurement stage using classification and regression tree(CART))

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至系統瀏覽論文 (2026-2-1以後開放)

摘要(中)

營建產業中，契約協商之結果可能決定專案成本效率，甚至提升營造廠之執行績效。本研究採用分類與回歸決策樹 (Classification and Regression Tree, CART) 預測協商結果之議價次數與減價幅度，以期在採購階段促成契約議價協商。本研究首先自過去文獻彙整交易特徵影響因素與總結適當之預測模型，並且蒐集近五年共計 10,470 筆營建專案契約協商原始資料。資料顯示工程專案地點大多位於臺灣北部地區，其中 90%為總價合同類型；交易特徵方面，議價次數介於 1 次至 5 次之間，減價幅度分布於 0%至 94%；依工程特性分類，可分為假設工程、地工工程、結構工程、外牆工程、內裝工程、門窗工程、設備機電工程、景觀工程與雜項工程。在議價次數與減價幅度之預測結果方面，準確度範圍分別介於 79.9%至 95.5%以及介於 55.6%至 86.9%之間。由於CART 模型之預測結果分布範圍較廣，依據進一步探討之預測結果，本研究可發展出 4個構面之策略，分別為議價次數多且減價幅度高、議價次數多卻減價幅度低、議價次
數少卻減價幅度高、以及議價次數少且減價幅度低，以輔助營造廠於採購階段調整議價協商策略。

摘要(英)

Contract negotiation may determine cost efficiency and even enhance performance to the general contractors in the construction industry. The research objective is to facilitate contract negotiation in the procurement stage using classification and regression tree (CART) in order to predict the negotiation quantity and price deduction margin. Firstly, the literature review summarizes the impact factors and proper prediction model, followed by the data collection within recent 5 years, resulting in 10,470 raw datasets of contract negotiation for construction projects. These data present the project locations mainly in the north Taiwan and 90% among them with the lump sum contract type. The data range for negotiation quantity is from 1 to 5 times and for price deduction margin is from 0% to 94%. There are 9 project categories involving falsework, earthwork, structure, wall, interior work, window, facility installation, landscape, and miscellaneous work. The prediction results on both negotiation quantity and price deduction margin are with the accuracies from 79.9% to 95.5% and from 55.6% to 86.9%, respectively. Since the results yielded form CART vary in wide ranges, the findings are interpreted further to develop negotiation strategies for general contractors in 4 aspects of high negotiation quantity with high price deduction margin, high negotiation quantity with low price deduction margin, low negotiation quantity with high price deduction margin, and low negotiation quantity with low price deduction margin.

關鍵字(中)

★ 契約協商
★ 減價幅度
★ 決策樹(CART)
★ 預測
★ 營建專案

關鍵字(英)

★ contract negotiation
★ price deduction
★ decision tree (CART)
★ prediction
★ construction project

論文目次

第一章緒論............1
1.1 研究背景與動機.....1
1.2 研究問題...........2
1.3 研究目的...........2
1.4 研究範圍與限制.....2
1.5 研究方法.........3
1.6 研究流程.......4
第二章文獻回顧.........6
2.1 營建發包與採購流程..........6
2.1.1 工程發包模式.......6
2.1.2 採購流程..........10
2.2 營建報價.....13
2.2.1 報價.......13
2.2.2 單價分析......18
2.3 營建議價........21
2.3.1 議價過程與互動.......21
2.3.2 雙方交易人特質與議價影響因素.......24
2.3.3 議價策略與議題.......28
2.4 營建數據與資料探勘.......31
2.4.1 營建數據.......31
2.4.2 資料探勘.........33
2.4.3 決策樹演算法.........37
2.4.4 其他分類演算法........42
2.4.5 混淆矩陣(Confusion matrix)........46
2.5 小結.......................47
第三章資料蒐集與分析.......49
3.1 資料蒐集................49
3.1.1 資料來源.............49
3.1.2 資料性質..............49
3.2 資料分析與處理...........54
3.2.1 資料分析............54
3.2.2 資料前處理............55
第四章模型建構............61
4.1 建構模型流程............61
4.1.1 節點分割..........62
4.1.2 剪枝原則..........63
4.2 模型預測結果..........67
4.2.1 議價次數之預測結果.......67
4.2.2 減價幅度之預測結果...69
4.3 預測結果討論...72
4.3.1 協商情境.......72
4.3.2 應對策略.......73
4.3.3 小結.......78
第五章結論與建議.......79
5.1 結論.......79
5.2 貢獻......80
5.3 建議.....82
參考文獻....83

參考文獻

[1] 李秉展, 羅紫萍, 王翊蘅, and 張玉萍, "人工智慧在土木工程領域各階段之應用," 技師期刊, no. 79, pp. 33-38, 2017.
[2] S. K. Sears, G. A. Sears, R. H. Clough, J. L. Rounds, and R. O. Segner, Construction project management. John Wiley & Sons, 2015.
[3] S. T. Ng and W. Li, "A parallel bargaining protocol for automated sourcing of construction suppliers," Automation in Construction, vol. 15, no. 3, pp. 365-373, 2006.
[4] R. H. Clough, G. A. Sears, and S. K. Sears, Construction project management. John Wiley & Sons, 2000.
[5] 廖嘉鴻, "營建採購協商紙上訓練遊戲之研究," 2009.
[6] C.-F. Haung, "營造業分包管理策略中班底效應之研究," National Central University,2000.
[7] 侯籹廷, "以分包商角度探討對營造廠報價行為策略之研究," National Central University, 2022.
[8] Y.-D. Lee, "運用關聯法則探討協力廠商對營造廠報價行為之研究," National Central University, 2022.
[9] C.-h. Chung, "透天住宅成本估算模式之研究," National Central University, 2010.
[10] M. Beer, M. d′Inverno, M. Luck, N. Jennings, C. Preist, and M. Schroeder, "Negotiation in multi-agent systems," The Knowledge Engineering Review, vol. 14, no. 3, pp. 285-289,
1999.
[11] H. Raiffa, The art and science of negotiation. Harvard University Press, 1982.
[12] S. B. Bacharach and E. J. Lawler, "Bargaining: Power, tactics, and outcomes," 1981.
[13] H. Lai, "A theoretical basis for negotiation support systems," Purdue University, 1989.
[14] Y. Zhang, H. Luo, and Y. He, "A system for tender price evaluation of construction project based on big data," Procedia Engineering, vol. 123, pp. 606-614, 2015.
[15] E. E. Cardella, "An investigation of behavioral influences in strategic decision making," The University of Arizona, 2012.
[16] C. Zhang, X. V. Zheng, and J. J. Li, "Is collaboration a better way to develop trust after opportunism? Distinguishing firm and boundary spanner opportunism," Industrial
Marketing Management, vol. 82, pp. 38-51, 2019.
[17] 鄧勝軒, "公共工程招標及履約階段之法律經濟分析," 2020.
[18] F. Giacobbe, Z. Matolcsy, and J. Wakefield, "An investigation of wholly-owned foreign subsidiary control through transaction cost economics theory," Accounting & Finance,vol. 56, no. 4, pp. 1041-1070, 2016.
[19] T. Y. Choi and D. R. Krause, "The supply base and its complexity: Implications for transaction costs, risks, responsiveness, and innovation," Journal of operations
management, vol. 24, no. 5, pp. 637-652, 2006.84
[20] 王國武 and 余文德, "工程異質採購分析模式之研究," 中國土木水利工程學刊, vol.23, no. 1, pp. 77-91, 2011.
[21] T.-P. Liang and H.-S. Doong, "Effect of bargaining in electronic commerce," International
Journal of Electronic Commerce, vol. 4, no. 3, pp. 23-43, 2000.
[22] 王忠宗, 採購管理. 日正企管顧問, 2000.
[23] C. Beam and A. Segev, "Electronic catalogs and negotiations," Fisher Center for Information Technology and Management Working Paper, 1996.
[24] 林育群 and 曾仁杰, "智慧型代理人應用於營建採購協商之研究," 2002.
[25] J.-S. Chou, C.-F. Tsai, and Y.-H. Lu, "Project dispute prediction by hybrid machine learning techniques," Journal of Civil Engineering and Management, vol. 19, no. 4, pp. 505-517,2013.
[26] B. Esmaeeli, M. Ravanshadnia, and M. Banki, "The assessment of bidding strategy of Iranian construction firm," in 2007 IEEE International Conference on Industrial Engineering and Engineering Management, 2007: IEEE, pp. 984-988.
[27] D. T. Pham and A. A. Afify, "Machine-learning techniques and their applications in manufacturing," Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture, vol. 219, no. 5, pp. 395-412, 2005.
[28] H.-T. T. Webinar, "Big Data Opportunities in Vertical Industries," Gartner Group, 2012.
[29] M. Usama, "Advances in knowledge discovery and data mining," 1996.
[30] M. J. Norton, "Knowledge discovery in databases," Library Trends, vol. 48, no. 1, p. 9,1999.
[31] S. Laxman and P. S. Sastry, "A survey of temporal data mining," Sadhana, vol. 31, no. 2,pp. 173-198, 2006.
[32] S. Mitra, S. K. Pal, and P. Mitra, "Data mining in soft computing framework: a survey,"IEEE transactions on neural networks, vol. 13, no. 1, pp. 3-14, 2002.
[33] A. K. Choudhary, J. A. Harding, and M. K. Tiwari, "Data mining in manufacturing: a review based on the kind of knowledge," Journal of Intelligent Manufacturing, vol. 20, no. 5, pp. 501-521, 2009.
[34] 包晃豪, "決策樹運用於工程查核選案之研究," 2010.
[35] S. Singh and P. Gupta, "Comparative study ID3, cart and C4. 5 decision tree algorithm: a survey," International Journal of Advanced Information Science and Technology (IJAIST), vol. 27, no. 27, pp. 97-103, 2014.
[36] L. Rokach and O. Maimon, "Decision trees," in Data mining and knowledge discovery handbook: Springer, 2005, pp. 165-192.
[37] P.-N. Tan, M. Steinbach, and V. Kumar, Introduction to data mining. Pearson Education India, 2016.
[38] W. Peng, J. Chen, and H. Zhou, "An implementation of ID3-decision tree learning algorithm," From web. arch. usyd. edu. au/wpeng/DecisionTree2. pdf Retrieved date: 85 May, vol. 13, 2009.
[39] S. Ding, H. Li, C. Su, J. Yu, and F. Jin, "Evolutionary artificial neural networks: a review," Artificial Intelligence Review, vol. 39, no. 3, pp. 251-260, 2013.
[40] X. Lin and Y. Lu, "Research on mathematical model of cost budget in the early stage of assembly construction project based on improved neural network algorithm,"Mathematical Problems in Engineering, vol. 2020, 2020.
[41] K. Tijanić, D. Car-Pušić, and M. Šperac, "Cost estimation in road construction using artificial neural network," Neural Computing and Applications, vol. 32, no. 13, pp.9343-9355, 2020.
[42] A. Pradhan, "Support vector machine-a survey," International Journal of Emerging Technology and Advanced Engineering, vol. 2, no. 8, pp. 82-85, 2012.
[43] J. Cervantes, F. Garcia-Lamont, L. Rodríguez-Mazahua, and A. Lopez, "A comprehensive survey on support vector machine classification: Applications, challenges and trends," Neurocomputing, vol. 408, pp. 189-215, 2020.
[44] L. Breiman, "Random Forests," Machine Learning, vol. 45, no. 1, pp. 5-32, 2001/10/01 2001, doi: 10.1023/A:1010933404324.
[45] Z. M. Yaseen, Z. H. Ali, S. Q. Salih, and N. Al-Ansari, "Prediction of risk delay in construction projects using a hybrid artificial intelligence model," Sustainability, vol. 12, no. 4, p. 1514, 2020.
[46] Z. M. Yaseen et al., "A novel hybrid evolutionary data-intelligence algorithm for irrigation and power production management: application to multi-purpose reservoir systems," Sustainability, vol. 11, no. 7, p. 1953, 2019.
[47] R. Rudžianskaitė–Kvaraciejienė, R. Apanavičienė, and A. Gelžinis, "Modelling the effectiveness of PPP road infrastructure projects by applying random forests," Journal of Civil Engineering and Management, vol. 21, no. 3, pp. 290-299, 2015.
[48] R. Wang, V. Asghari, C. M. Cheung, S.-C. Hsu, and C.-J. Lee, "Assessing effects of economic factors on construction cost estimation using deep neural networks," Automation in Construction, vol. 134, p. 104080, 2022.
[49] D. J. Lowe, M. W. Emsley, and A. Harding, "Predicting construction cost using multiple regression techniques," Journal of construction engineering and management, vol. 132,
no. 7, pp. 750-758, 2006.
[50] P. Blajdo, J. W. Grzymala-Busse, Z. S. Hippe, M. Knap, T. Mroczek, and L. Piatek, "A comparison of six approaches to discretization—a rough set perspective," in International Conference on Rough Sets and Knowledge Technology, 2008: Springer, pp.31-38.
[51] J. W. Grzymala-Busse, Z. S. Hippe, and T. Mroczek, "Reduced Data Sets and EntropyBased Discretization," Entropy, vol. 21, no. 11, p. 1051, 2019.

指導教授

陳介豪(Jieh-Haur Chen)

審核日期

2023-1-19

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