背景與目的:企業資本支出決定未來發展, 避險採購策略在物流、金流、資訊流快速流轉的時代，避險採購策略在原物成本佔整體公司營運成本的最大比率的製造業，己成為公司決勝，甚至是能否生存的關鍵因素。如何運用建築資訊建模(BIM)和大數據(Big data)進行控管成本及預測原料-銅的變化，為本研究主軸.

研究方法: 大數據分析銅價預測模型建構過程，並代入BIM系統的BOM展開。主要運用個案已開發之FIES系統，結合市場Open data_49項指標和銅現價,以SPSS 12.0迴歸分析，以找出預判銅價未來趨勢的方法及指標.

研究結果: 大數據分析建構銅價預測模型，以下一期銅價為準則(依)變項，以逐步廻歸分析逐步選入預測(自)變項，以建構銅價預測模型經建模與數據分析最終萃取出銅價(當日)、美元兌日幣匯率、美國恐慌指數、金價，等四個變項，並確立模型廻歸係數，預測模型R-sq為.992

結論與建議:將本結論進行結合採購避險策略運用及大數據分析對未來趨勢，進行預測及管理風險規避,，故在導入大數據模式預估後，在實務上可運用其它指標來提前預測變化，針對其發生機率模擬相對應策略做到應形無窮.

Procurement hedge strategies is a key factor for survival in rapid circulation of logistics, gold flow and information flow in the manufacturing industry where the original cost accounts for the largest proportion of the overall company's operating cost. The enterprise resource planning (ERP) and material resource planning (MRP) system and its expanded bills of materials (BOM) are the key methods for controlling the procurement costs of raw material.
In large-scale manufacturing, the Building Information Modeling (BIM) are deployed in layout process and the bill of materials for raw material cost control are deployed at the same time. Specially, the unit price of materials is established with the BIM system is completed in the initial stage. But the prices of raw materials fluctuate with the fluctuation of the international economy at the correct time for material demand. The impact of price fluctuations in related raw material may far exceed the evaluation with BOM. Therefore, the mastery of price fluctuation in raw material and the prediction of price fluctuation become the key tasks of hedging procurement.
Since copper is the main material for a factory in layout phase. This study aims to predict the price of copper using big data analysis, develop the hedging procurement strategies, feedback the strategies to the BIM system for smart purchasing. This study also adopts case study to verify the model in practice. The results show that the model for predicting the price of copper trained with big data has a good fitness with actual data and it is helpful to develop the hedging procurement strategies. In practice, the hedging procurement strategies are helpful to the company for reducing the risk, cost, and lifting the profits in operation with the case study.

英文文獻
Aharon, D. Y., & Qadan, M. (2018). What drives the demand for information in the commodity market? Resources Policy, 59, 532-543.
Biro, Z. M., Bartok, A., Sipos, F. Z., Sarkany, N., Horvath, R., Ducz, M., . . . Mittweg, G. (2019). Bill of material based predecessor product determination in demand planning. In: Google Patents.
Buck-Emden, R., & Galimow, J. (1996). SAP R/3 System-A Client/Server Technology.
Chen, I. J. (2001). Planning for ERP systems: analysis and future trend. Business process management journal, 7(5), 374-386.
Christensen, J. K. (2018). Using BIM as a tool to decrease variation in quantity and optimize the workflow of generating a cost estimation. BUILDING INFORMATION MODELING (BIM).
Chung, B., Skibniewski, M. J., & Kwak, Y. H. (2009). Developing ERP systems success model for the construction industry. Journal of construction engineering and management, 135(3), 207-216.
Cooper, M. C., & Ellram, L. M. (1993). Characteristics of supply chain management and the implications for purchasing and logistics strategy. The international journal of logistics management, 4(2), 13-24.
Dallasega, P. (2018). Industry 4.0 fostering construction supply chain management: Lessons learned from engineer-to-order suppliers. IEEE Engineering Management Review, 46(3), 49-55.
Economics Trading. (2019). United States Inflation Rate.
https://tradingeconomics.com/united-states/inflation-cpi.
Erdoğdu, A. (2017). The Most Significant Factors Influencing the Price of Gold: An Empirical Analysis of the US Market. Economics, 5(5), 399-406.
Eryiğit, M. (2017). Short-term and long-term relationships between gold prices and precious metal (palladium, silver and platinum) and energy (crude oil and gasoline) prices. Economic research-Ekonomska istraživanja, 30(1), 499-510.
Farizi, A., S., & Latief, Y. (2018). Development of standardized WBS (Work Breakdown Structure) for planning the schedule based on risk in Steel Bridge construction projects. Paper presented at the 8th International Conference on Industrial Engineering and Operations Management, IEOM 2018.
Firouzi, A., & Vahdatmanesh, M. (2019). Applicability of Financial Derivatives for Hedging Material Price Risk in Highway Construction. Journal of construction engineering and management, 145(5), 04019023.
Ford, D. (1980). The development of buyer-seller relationships in industrial markets. European Journal of Marketing, 14(5/6), 339-353.
FRED. (2019a). 10-Year Treasury Constant Maturity Rate (DGS10). Retrieved from https://fred.stlouisfed.org/series/DGS10/
FRED. (2019b). CBOE Volatility Index: VIX (VIXCLS). Retrieved from https://fred.stlouisfed.org/series/VIXCLS
FRED. (2019c). Consumer Price Index for All Urban Consumers: All Items in U.S. City Average (CPIAUCSL). Retrieved from https://fred.stlouisfed.org/series/CPIAUCSL
Globerson, S. (1994). Impact of various work-breakdown structures on project conceptualization. International Journal of Project Management, 12(3), 165-171.
Google Trends. (2019a). Copper prices. Retrieved from
https://trends.google.com/trends/explore?date=all&q=copper%20prices
Google Trends. (2019b). Gold prices. Retrieved from
https://trends.google.com/trends/explore?date=all&q=GOLD%20PRICES
Google Trends. (2019c). QE1. Retrieved from
https://trends.google.com/trends/explore?date=all&q=QE1
Google Trends. (2019d). Silver prices. Retrieved from
https://trends.google.com/trends/explore?date=all&q=SILVER%20PRICES
He, K., Chen, Y., & Tso, G. K. (2017). Price forecasting in the precious metal market: A multivariate EMD denoising approach. Resources Policy, 54, 9-24.
Hegge, H., & Wortmann, J. (1991). Generic bill-of-material: a new product model. International Journal of Production Economics, 23(1-3), 117-128.
Hillson, D. (2003). Using a risk breakdown structure in project management. Journal of Facilities management, 2(1), 85-97.
Investing.com. (2019). Copper Futures.
https://www.investing.com/commodities/copper-historical-data, November 2019.
Jung, Y., & Joo, M. (2011). Building information modelling (BIM) framework for practical implementation. Automation in construction, 20(2), 126-133.
Jung, Y., & Woo, S. (2004). Flexible work breakdown structure for integrated cost and schedule control. Journal of construction engineering and management, 130(5), 616-625.
Krawczyńska-Piechna, A. (2014). A concept of an integrated construction planning system involving location-based scheduling technique. Czasopismo Techniczne.
Kumar, S. (2017). On the nonlinear relation between crude oil and gold. Resources Policy, 51, 219-224.
LBMA. (2019). Precious Metals Prices. Retrieved from http://www.lbma.org.uk/precious-metal-prices
Lin, J.-Y. (2014). Explore the Determinations of price movements for Gold and Silver. Master Thesis of Tunghai University Institutional Repository, 2014.
Luo, J., & Chen, X. (2017). Risk hedging via option contracts in a random yield supply chain. Annals of Operations Research, 257(1-2), 697-719.
Macrotrends. (2019). Crude Oil Futures - Price & Chart. Retrieved from https://www.macrotrends.net/futures/crude-oil
Monczka, R. M., Handfield, R. B., Giunipero, L. C., & Patterson, J. L. (2015). Purchasing and supply chain management: Cengage Learning.
Ocheoha, I. A., & Moselhi, O. (2018). A BIM-based Supply Chain Integration for Prefabrication and Modularization. Modular and Offsite Construction (MOC) Summit Proceedings, 1(1).
Petrisor, I., & Cozmiuc, D. (2020). Global supply chain management organization at siemens in the advent of industry 4.0. In Supply Chain and Logistics Management: Concepts, Methodologies, Tools, and Applications (pp. 1095-1114): IGI Global.
Ptak, C. A., & Schragenheim, E. (2003). ERP: tools, techniques, and applications for integrating the supply chain: Crc Press.
Pučko, Z., Šuman, N., & Klanšek, U. (2014). Building information modeling based time and cost planning in construction projects. Organization, technology & management in construction: An International Journal, 6(1), 0-0.
Rich, N., & Hines, P. (1997). Supply-chain management and time-based competition: the role of the supplier association. International Journal of physical distribution & logistics management, 27(3/4), 210-225.
Rose, K. H. (2006). Book Review: Practice Standard for Work Breakdown Structures—Second Edition: By Project Management Institute. In: SAGE Publications Sage CA: Los Angeles, CA.
Saad, M., Jones, M., & James, P. (2002). A review of the progress towards the adoption of supply chain management (SCM) relationships in construction. European Journal of Purchasing & Supply Management, 8(3), 173-183.
Saoud, L. A., Omran, J., Hassan, B., Vilutienė, T., & Kiaulakis, A. (2017). A method to predict change propagation within building information model. Journal of Civil Engineering and Management, 23(6), 836-846.
Siemon, M., Schiffer, M., & Walther, G. (2019). Integrated Purchasing and Production Planning for a Non-Ferrous Metal Production Network. Omega, 102136.
Stefanou, C. (1999). Supply chain management (SCM) and organizational key factors for successful implementation of enterprise resource planning (ERP) systems. AMCIS 1999 proceedings, 276.
Succar, B. (2009). Building information modelling framework: A research and delivery foundation for industry stakeholders. Automation in construction, 18(3), 357-375.
Tausworthe, R. C. (1979). The work breakdown structure in software project management. Journal of Systems and Software, 1, 181-186.
Taylor, M. D. (2003). How to Develop Work Breakdown Structures
Teltumbde, A. (2000). A framework for evaluating ERP projects. International Journal of Production Research, 38(17), 4507-4520.
Trandigeconomics. (2019). United States Money Supply M1. Retrieved from https://tradingeconomics.com/united-states/money-supply-m1
Umble, E. J., Haft, R. R., & Umble, M. M. (2003). Enterprise resource planning: Implementation procedures and critical success factors. European Journal of Operational Research, 146(2), 241-257.
Wang, M., Altaf, M. S., Al-Hussein, M., & Ma, Y. (2018). Framework for an IoT-based shop floor material management system for panelized homebuilding. International Journal of Construction Management, 1-16.
Wikipedia. (2019). Supply Chain Management.
https://zh.wikipedia.org/wiki/%E4%BE%9B%E5%BA%94%E9%93%BE%E7%AE%A1%E7%90%86, 2019.
Wu, Q., & Chen, A. (2015). Optimal combined purchasing strategies for a risk-averse manufacturer under price uncertainty. Journal of Industrial Engineering and Management (JIEM), 8(4), 1087-1102.
Yahoo, F. (2019). Dow Jones Industrial Average.
https://finance.yahoo.com/quote/%5Edji/history?ltr=1.
You, Z., & Wu, C. (2019). A framework for data-driven informatization of the construction company. Advanced Engineering Informatics, 39, 269-277.
Zhou, C., & Cao, Q. (2018). Design and implementation of intelligent manufacturing project management system based on bill of material. Cluster Computing, 1-9.

中文文獻
王碩彥。(2019)。新建住宅工程專案內部裝修作業排程之研究。臺灣大學土木工程學研究所碩士學位論文，1-79。
吳建璋。(2019)。點時成金!大數據因果分析法於貴金屬策略採購之研究。成功大學高階管理碩士在職專班(EMBA)學位論文(2019年)，1-60。
武漢天帷BIM服務專家。(2017)。BWS和BIM項目管理。科技每日頭條，https://kknews.cc/tech/bongeno.html。
邱桂珍、黃悅民、鄭育評。(2018)。結合系科就業職能於創意與創新課程啟發工程學生創作產品。工程技術與科技教育學術研討會，68-79。
鉅亨網。(2019a)。Aberdeen Standard Physical Platinum Shares ETF (PPLT)。 Retrieved from
https://www.cnyes.com/usastock/history.aspx?code=PPLT&qm_page=36896。
鉅亨網。(2019b)。Historical Data for iShares Silver Trust。
https://stage.cnyes.com/usastock/history.aspx?code=SLV&qm_page=90395。
鉅亨網。(2019c)。SPDR Gold Trust (GLD). Retrieved from
https://www.cnyes.com/usastock/history.aspx?code=GLD&qm_page=33126。
鉅亨網。(2019d)。銅礦ETF。Retrieved from
https://www.cnyes.com/usastock/etfs_price/COPX.html。
臺灣期貨交易所。(2019)。每日外幣參考匯率查詢。Retrieved from
https://www.taifex.com.tw/cht/3/dailyFXRate。