工程技術顧問業於國家經濟發展及重大公共建設上佔有極重要角色，其素質及經營環境之健全與否，皆直接影響工程品質與安全。目前於台灣其面臨雖有資金需求卻無良好之融資方式與概念，而金融機構亦對於工程技術顧問業之了解相當有限，造成工程技術顧問業融資困難。因此本研究採用修正式德菲法訪談35位雙方產業專家、召開專家座談會促使其互相了解，並共同訂定問卷之內容；再針對雙方產業進行母體發放問卷1124份，有效回收233份。回收後運用SPSS進行「遺漏檢驗」、「敘述性統計」、「極端組比較」、「同質性檢驗」、「一致性檢驗」共計五類九項之因素分析法，確立14項工程技術顧問業與金融業之重要融資影響因子。而後進行主成分分析，經過因素轉軸後將14項融資因子萃取成4項群組，此四項群組分別為「融資借貸說明」權重為0.328、「公司過往能力說明」為0.270、「工程說明與其他」為0.214、「融資抵押品」為0.188，最後針對群組特性提出相關之融資所需文件，提供工程技術顧問業後續進行融資之重要參考依據，使工程技術顧問業了解金融機構評估放款所重視之方向，並使金融機構可根據四群組之權重排序調整工程技術顧問業之融資標準。

The Taiwan financial institutions utilizing uniform criteria in financing decisions for all industries have impeded strong financial endorsement of engineering consulting firms. The purposes of this research are to identify the factors that influence the financing mechanism so as to raise financing practicability, and to establish fitting financing criteria for engineering consulting firms. An initial survey was conducted with participation of 118 professionals serving in the both financial and engineering consulting markets, and summarized 36 points influencing financing mechanism. To determine significance and fitting criteria of financing, a comprehensive analysis using questionnaire and factor analysis to the population, 691 engineering consulting firms and 433 financial institutions, concluded 14 significant factors classified as 4 principle criteria: repayment and purpose with weight of 0.328, corporation perspective with weight of 0.270, engineering project description with weight of 0.214, and financing protection with weight of 0.188. Finally, the corresponding documents were also suggested.

參考文獻
1. 王保進 (2004)，多變量分析-套裝程式與資料分析，高等教育出版社。
2. 邱皓政 (2000)，量化分析與統計分析，五南圖書出版公司。
3. 陳介豪 (2005)，建立金融體系與工程顧問業合作機制之研究，行政院公共工程委員會。
4. Ahuja, H. (1976). Construction performance control by networks, Wiley, New York.
5. Anonymous (1996). US power developer calls on banks, multilaterals to re-think IPP financing, International Trade Finance. London, 273, 3-5.
6. Asamow, E. (1995). Measuring the Hidden Risk in Corporate,” Commercial Leanding Review 10(1), 24-32.
7. Bodenhorn, H. (2003). Short-Term Loans and Long-Term Relationships: Relationship Lending in Early America, Journal of Money, Credit, and Banking, 35(4), 485-505.
8. Capon, N. (1982). Credit Scoring System: A Critical Analysis, Journal of Marketing, 46(1), 82-91.
9. Comrey, A. L. (1973). A first course in factor analysis. New York: Academic Press.
10. Davies, N., Sharma, T. (1995). Factor analysis of schizophrenic symptoms 15(1-2), 21.
11. Diertrich, J. R., Robert, S. K. (1982). Empirical Analysis of the Commerical Loan Classification Decision, The Accounting Review, 57, 18-38.
12. Gorsuch, R. L. (1983). Factor analysis. Hillsdale, NJ: Lawrence Erlbaum.
13. Hair, J. F. Jr., Anderson, R. E., Tatham, R. L., Black, W. C. (1998). Multivariate data analysis. Upper Saddle River, NJ: Prentice-Hall.
14. Harman, H. H. (1976). Modern factor analysis (3rd ed.). Chicago: University of Chicago Press.
15. Harman, H. H. & Jones, W. H. (1963). Factor analysis by minimizing rediduals. Psychometrika, 30, 351-368.
16. Hill, K. Q., Fowles, J. (1975). The methodological worth of the Delphi forecasting technique. Technological Forecasting and Social Change, 7, 179-192.
17. Hoon, Lim Siong, Sargent, Sarah. Asiamoney (1995). The battle for Bakun, London: 6(2), 25-32.
18. Hubbard, R. G., Kuttner, K.N., and Palia, D.N. (2002). Are There Bank Effects in Borrowers’ Costs of Funds? Evidence from a Matched Sample of Borrowers and Banks, The Journal of Business, 75(4), 559-582.
19. Kaiser, H. F. (1959). The application of electronic computers to factor analysis. Symposium on the Application of Computers to Psychological Problems, APA.
20. Kaiser, H. F. (1963). Image analysis. In C. W. Harman (Ed.), Problems in measuring change, Madison: University of Madison Press, 156-166.
21. Kaiser, H. F. (1970). A second-generation Little Jiffy. Psychometrika, 35, 401-415.
22. Kaiser, H. F. (1974). Little Jiffy, Mark IV. Educational and Psychometrika Measurement, 34, 111-117.
23. Kaiser, H. F. & Caffrey, J. (1965). Alpha factor analysis. Psychometrika, 30, 1-14.
24. Kim, J. O. & Mueller, C. W. (1978). Introduction to factor analysis: What it is and how to do it. Newbury Park, CA: Sage.
25. Kim, J. O. & Mueller, C. W. (1978). Factor analysis: Statistical methods and practical issues. Newbury Park, CA: Sage.
26. Linstone, H. A., Turoff, M. (1975). The Delphi method: techniques and applications, Addison-Wesley, London.
27. Lock, A. (1987). Integrating group judgements in subjective forecasts. In: Wright, G., & Ayton, P (Eds.), Judgemental forecasting, Wiley, Chichester.
28. Parente, F. J., Anderson-Parente, J. K. (1987). Delphi inquiry systems. In: Wright, G., & Ayton, P (Eds.), Judgemental forecasting, Wiley, Chichester.
29. Price A. D. F., Shawa, H. (1997). Survey of Project Related Finance in United Arab Emirates, Journal of Construction Engineering and Management, 123(3), 223-232.
30. Riding, A.L., Haines, Jr. G. (2001). Loan Guarantees: Costs of Default and Benefits to Small Firms, Journal of Business Venturing, 16(6), 595-612.
31. Rowe, G., Wright, G., and Bolger, F. (1991). The Delphi technique: a re-evaluation of research and theory. Technological Forecasting and Social Change, 39(3), 235-251.
32. Rowe, G., Wright, G. (1999). The Delphi technique as a forcasting tool: issues and analysis. International Journal of Forecasting, 15, 353-375.
33. Shawa H. H. (1995). Project related for construction contractors in the united Arab Emirates, PhD thesis, Loughborough University, U.K.
34. Srinivasan, V., Kim, Y. H. (1988). Designing Expert Financial Systems-A Case Study of Corporate Credit Management, Financial Management, 17(3), 32-45.
35. Stewart, T. R. (1987). The Delphi technique and judgmental forecasting, Climatic Change, 11, 97-113.
36. Thoefner, M. B., Ersboll, A. K., Jensen, A. L., Hesselholt, M. (2000). Factor analysis of the interrelationships between clinical variables in horses with colic, Preventive Veterinary Medicine 48(3), 201-214.
37. West, R. C. (1985). A Factor Analytic Approach to Bank Condition, Journal of Banking and Finance, 15(1), 253-226.
38. Whalen, G. W., Thomson, J. B. (1998). Using Financial Data to Identify Changes in Bank Condition, Economics Review, Federal Reserve Bank of Cleveland, 2nd Quarter, 18, 17-26.