營建專案之人事費用支出向來即為營建公司重點議題之一，於專案備標階段即需準確評估，倘無法確估人事費用預算，將直接影響得標專案獲利空間，本研究鑑於過往營建專案人力配置並無明確方法或原則可依循，故欲建立一套可有效推估營建專案人力配置數量及參與時序之模式。首先本研究透過文獻回顧方式瞭解影響營建專案人力配置之主要原因為何以及如何借助資料探勘及人工智慧等方式建立預測模式，爾後再透過專家訪談及改良式德爾菲法建構欲蒐集營建專案案例之資料型式。透過國內數家大型營建公司協助，蒐集台灣近十六年來共計一百二十九筆營建專案工程案例，經由敘述性統計分析可得出影響營建專案人力配置之關鍵因素共有十六項，同時並篩選完整案例共計九十七筆作為日後可供存取之案例資料庫。其後，本研究借助案例式推理(case based reasoning, CBR)及時間序列(Time Series)分析模式建立營建專案工程人力配置預測模式，此模式之特色為可依據營建專案各項表徵資訊及各種估算成本即可預測投入專案之人數，並可得到各類型專業人員特有之參與時序曲線，此曲線將可作為專案配置各專業人員時序之參考。最後本研究將建立之預測模式採用三次交叉驗證方式(Three-Way Cross Validation)進行驗證以佐證本研究之價值，由其結果得知此模式之正確率高達88.65%，表示其已足有參考之價值。本研究並發現十六項關鍵因素中，皆屬專案規劃前期可得知之資訊，故本模式將可於新專案前期規劃時，即可輸入各項資訊預測所需之人力並可建構專案各階段各種專業職能人員參與時序之策略。

In the highly competitive construction industry of Taiwan, a slightly inaccurate estimation of a project can easily cause loss of the bid, especially in erroneously estimating costs and allocation of on-site and off-site manpower that usually offsets the profit gained from the project and even jeopardizes the management processes of the project. This research developed a predict model based on mathematical regression, case-based reasoning and time series to predict costs and allocation of on-site and off-site manpower for construction projects. It is founded on laborious processes of data collections and analyses by matching statistical assumptions, and includes construction projects of residential buildings, industrial office buildings, commercial buildings and industrial construction. In this research, 97 cases data filtered by 129 Construction projects cases with Descriptive Statistics method would be used as proper data for analyzing via case based reasoning and Time Series, to establish an optimization model. After verifying by Three-way Cross Validation, the accuracy rate of this model achieved 88.65%. This research can be used in project bidding stage for estimating on-site and off-site manpower of each position of whole project life cycle.

〔1〕Bureau of construction, ministry of internal affairs.
〔2〕行政院公共工程委員會，政府採購法，民國100年。
〔3〕Belout, A. & Gauvreau, C., “Factors influencing project success: the impact of human resource management”, International journal of project management, 22(1), pp. 1-11, 2004.
〔4〕陳政賢，「營建業企業資源規劃導入分析模式之建構」，國立台灣大學土木工程學系，碩士論文，民國91年。
〔5〕Carty, G. J., “Construction”, Journal of Construction Engineering and Management, 121(3), pp. 319-328, 1995.
〔6〕盧仲昱，「營建工程契約遲延問題之研究」，私立東吳大學法律學研究所，碩士論文，34-36頁，民國83年。
〔7〕王明德，「工程契約糾紛與仲裁」，營建管理季刊，民國83年。
〔8〕徐慧怡，「定型化契約條款解釋之研究」，中興法學第22期，民國75年。
〔9〕鄧民治，「論工程契約爭議之仲裁」，中國文化大學法律學研究所，碩士論文，民國89年。
〔10〕建設業法研究會，公共工事標準請負契約約款解說，大成出版社，民國79年。
〔11〕Levin, P., Construction Contract, Claims, Changes and Dispute Resolution, ASCE Publications, 1998.
〔12〕McGreevy, S. L., “When you see a claim coming, prepare”, Contractor Magazine, 5(11), pp. 29-34, 2004.
〔13〕PMBoK, A., Guide to the project Management body of knowledge, Project Management Institute, Pennsylvania USA, 2000.
〔14〕Walton, R. E., et al., Human resource management: a general manager's perspective: text and cases, Free Press, 1985.
〔15〕Formbtun, C., Strategies HRM, Wiley, New York, 1984.
〔16〕Vetter, E. W., Manpower Planning for High Talent Personnel, University of Michigan, Printed in U.S.A., 1-4, 1967.
〔17〕Grinold, R. C., & Marshall, K. T., Manpower planning models, New York: North-Holland, 1977.
〔18〕范薏美，「人力資源規劃理論之研究」，台灣大學政治學系，未出版碩士論文，民國81年。
〔19〕Rich, E. & Knight, K., Artificial intelligence, Tata McGraw-Hill, 1991.
〔20〕 Xu, L. D., “Case based reasoning”, Potentials IEEE, 13(5), pp. 10-13, 1994.
〔21〕Jain, A. K., Mao, J. & Mohiuddin, K. M., “Artificial neural networks: A tutorial”, Computer, 29(3), pp. 31-44, 1996.
〔22〕Arditi, D., Oksay, F. E. &d Tokdemir, O. B., “Predicting the outcome of construction litigation using neural networks”, Computer‐Aided Civil and Infrastructure Engineering, 13(2), pp. 75-81, 1998.
〔23〕Tokdemir, O. B., “Using case‐based reasoning to predict the outcome of construction litigation”, Computer‐Aided Civil and Infrastructure Engineering, 14(6), pp. 385-393, 1999.
〔24〕 Lees, B., Hamza, M. & Irgens, C., “Case-based reasoning support for engineering design”, In Intelligent Systems and Smart Manufacturing, International Society for Optics and Photonics, pp. 394-402, 2000.
〔25〕LU, M. et al., “Research and development of case-based reasoning system of product-oriented process planning information”, Journal of Harbin Institute of Technology, 7, 041, 2005.
〔26〕Lotfy, E. A. & Mohamed, A. S., “Applying neural networks in case-based reasoning adaptation for cost assessment of steel buildings”, International journal of computers and applications, 24(1), pp. 28-38, 2002.
〔27〕黃英忠，現代人力資源管理，華泰書局，民國78年。
〔28〕Sikula, A. F., Personnel administration and human resources management, Wiley, 1975.
〔29〕Silcock, H., “The phenomenon of labour turnover”, Journal of the Royal Statistical Society, Series A (General), pp. 429-440, 1954.
〔30〕謝安田，人事管理，謝安田出版，159-219頁，民國80年。
〔31〕Cascio, W. F., Applied psychology in personnel management, 1987.
〔32〕Gary Dessler著，人事管理，陳海鳴譯，二版，華泰書局，77-87頁，民國72年。
〔33〕Edwards, J. S., “A survey of manpower planning models and their application”, Journal of the Operational Research Society, pp. 1031-1040, 1983.
〔34〕Murdick, R. G., Render, B. & Russell, R. S., “Service operations management”, Vol. 7, Boston: Allyn and Bacon, 1990.
〔35〕Forbes, A. F., Introduction to Wasp: a computerised wastage analysis package, Institute of Manpower Studies, Brighton, 1979.
〔36〕Forbers, A. F., “Non-paranetric Methods of Estimating the Survior Function”, Statistician, 20, pp. 27-52, 1971.
〔37〕Forbers, A. F., “Some Statistical Models and Techniques for Manpower Planning”, Ph.D. Thesis, University of Kent, 1974.
〔38〕Georgoff, D. M. & Murdick, R. G., Manager's guide to forecasting, Harvard Business Review, 1986.
〔39〕Chen, M. S., Han, J. & Yu, P. S., “Data mining: an overview from a database perspective”, Knowledge and data Engineering, IEEE Transactions on, 8(6), pp. 866-883, 1996.
〔40〕Agrawal, R., Faloutsos, C. & Swami, A., Efficient similarity search in sequence databases, Springer Berlin Heidelberg, pp. 69-84, 1993.
〔41〕Faloutsos, C., Ranganathan, M. & Manolopoulos, Y., “Fast subsequence matching in time-series databases”, ACM, 23(2), pp. 419-429, 1994.
〔42〕Faloutsos, C. & Lin, K. I., “FastMap: A fast algorithm for indexing, data-mining and visualization of traditional and multimedia datasets”, ACM, 24(2), pp. 163-174, 1995.
〔43〕Lin, R. A. K. L. & Shim, H. S. S. K., “Fast similarity search in the presence of noise, scaling, and translation in time-series databases”, VLDB, pp. 490-501, 1995.
〔44〕Bernad, D. J., Finding patterns in time series: a dynamic programming approach, Advances in knowledge discovery and data mining, 1996.
〔45〕Li, C. S., Yu, P. S. & Castelli, V., “Hierarchy scan: A hierarchical similarity search algorithm for databases of long sequences”, In Data Engineering Proceedings of the Twelfth International Conference on IEEE, pp. 546-553, 1996.
〔46〕Park, S., et al., “Efficient searches for similar subsequences of different lengths in sequence databases”, In Data Engineering Proceedings of 16th International Conference on IEEE, pp. 23-32, 2002.
〔47〕Park, S., Lee, D. & Chu, W. W., “Fast retrieval of similar subsequences in long sequence databases”, In Knowledge and Data Engineering Exchange (KDEX'99) Proceedings, Workshop on. IEEE, pp. 60-67, 1999.
〔48〕廖述賢，資訊管理，雙葉書廊，臺北市，民國96年。
〔49〕MacCallum, R. C., Psychology 820 course packet, 1999.
〔50〕Kim, J. O., & Mueller, C. W. (Eds.), Factor analysis: Statistical methods and practical issues, Vol. 14, Sage, 1978.
〔51〕Velicer, W. F. & Jackson, D. N., “Component analysis versus common factor analysis: Some issues in selecting an appropriate procedure”, Multivariate behavioral research, 25(1), pp. 1-28, 1990.
〔52〕Hamilton, J. D., Time series analysis, Vol. 2. Princeton: Princeton university press, 1994.
〔54〕Hagan, M. T. & Behr, S. M., “The time series approach to short term load forecasting”, Power Systems IEEE Transactions on, 2(3), pp. 785-791, 1987.
〔53〕Box, G. E., Jenkins, G. M. & Reinsel, G. C., Time series analysis: forecasting and control, John Wiley & Sons, 2013.
〔55〕Fu, T. C., “A review on time series data mining”, Engineering Applications of Artificial Intelligence, 24(1), pp. 164-181, 2011.
〔56〕Caporaso, J. G., et al., “QIIME allows analysis of high-throughput community sequencing data”, Nature methods, 7(5), pp. 335-336, 2010.
〔57〕Montgomery, D. C., Jennings, C. L. & Kulahci, M., Introduction to time series analysis and forecasting, Vol. 526, John Wiley & Sons, 2011.
〔58〕Lenz, M., et al., Case-based reasoning technology, from foundations to applications, Springer-Verlag, pp. 299-326, 1998.
〔59〕Chen, D. & Burrell, P., “Case-based reasoning system and artificial neural networks: A review”, Neural Computing and Applications, 10(3), pp. 264-276, 2001.
〔60〕Kim, J., Suh, W. & Lee, H., “Document-based workflow modeling: a case-based reasoning approach”, Expert systems with applications, 23(2), pp. 77-93, 2002.
〔61〕Tseng, H. E., Chang, C. C. & Chang, S. H., “Applying case-based reasoning for product configuration in mass customization environments”, Expert Systems with Applications, 29(4), pp. 913-925, 2005.
〔62〕Yau, N. J. & Yang, J. B., “Applications of case-based reasoning in construction engineering and management”, Congress on Computing in Civil Engineering, Proceedings, pp. 663-669, 1996.
〔63〕binti Abdullah, S., “The fundamentals of case-based reasoning: application to a building defect problem”, Malaysian Journal of Computer Science, 10(1), pp. 10-26, 1997.
〔64〕Li, H., “Case-based reasoning for intelligent support of construction negotiation”, Information and Management, 30(5), pp. 231-238, 1996.
〔65〕Shahhosseini, V. & Sebt, M. H., “Competency-based selection and assignment of human resources to construction projects”, Scientia Iranica,18(2), pp. 163-180, 2011.
〔66〕Sedighi, F. & Loosemore, M., “Employer-of-choice characteristics in the construction industry”, Construction Management and Economics, 30(11), pp. 941-950, 2012.
〔67〕Liao, P. W. & Hsu, L. C., Engineers’ manpower quality promotion and arrangement plan model: A Case of the Fu Tsu Construction Company, 2014.
〔68〕Lexis-Nexis Academic Universe, Legal Research Database, Reed Elsevier Inc., 2002.
〔69〕Arditi, D. & Tokdemir, O. B., “Comparison of case-based reasoning and artificial neural networks”, Journal of computing in civil engineering, 13(3), pp. 162-169, 1999.
〔70〕Yau, N. J. & Yang, J. B., “Case‐based reasoning in construction management”, Computer‐Aided Civil and Infrastructure Engineering, 13(2), pp. 143-150, 1998.
〔71〕Harvey, A. C., & Harvey, A. C., Time series models, Vol. 2, Harvester Wheat sheaf, New York, 1993.
〔72〕Kwong, C. K., Smith, G. F. & Lau, W. S., “Application of case based reasoning injection moulding”, Journal of Materials Processing Technology, 63(1), pp. 463-467, 1997.
〔73〕Kohavi, R., “A study of cross-validation and bootstrap for accuracy estimation and model selection”, In IJCAI, 14(2), pp. 1137-1145, 1995.
〔74〕Wiens, T. S., et al., “Three way k-fold cross-validation of resource selection functions”, Ecological Modelling, 212(3), pp. 244-255, 2008.