【正文】 the worker is not employed by the firm, but is managed more or less as if they were an employee. This pratice is so mon in IT that the presence of contract employees is assumed to be a standard feature of IT departments. At the next level is selective outsourcing in which a firm outsources particular projects or parts of projects to an outside vendor. This is also quite mon in software development and technical support activities, although any welldefined task could presumably be outsourced in this way. Finally, the firm may choose to outsource the entire IT function, a practice that began in the late 1980s and has continued today. Hitt, Lorin M., Frei, Frances X. and Patrick T. Harker. (1999) How Financial Firms Decide on Technology, in Brookings/Wharton Papers on Financial Services:1999, Litan, Robert E. and Anthony M. Santomero, Eds. Washington, DC: Brookings Institution Press. 11 / 11。 a firm calculates the present value of the investment using all the ponents that can be quantified and then pares this prliminary value to the qualitative list of other benefits and costs. In other cases, where the evaluation is make difficult because of future uncertainties (. market growth and acceptance。 Clemens (1991) terms this the trap of the vanishing status quo.　　For the quantative financial evaluation, most IT evaluation methods have their roots in traditional capital budgeting procedures such as discounted cash flow analysis(DCF). However, while these techniques can work well for projects where costs and benefits ar well defined (. purchasing offthe shelf software in pursuit of operational cost savings), it is increasingly recognized that simple application of DCF approaches is not sufficient for IT investments. This is because much of the value of modern IT investments is likely to be difficult to quantify such as revenue enhancements or cost savings through improved customer service, product variety, or timeliness. One monly used stategy is to value nonquantifiable benefits at zero, although this strategy will systematically bias project evaluations to unnecessarily reject projects. 　　Recognizing the limitation of the DCF approach, several alternative approaches have been proposed. One method is to base tghe case entirely on qualitative analysis。 they argue that information systems specialists should be reponsible for evalusting new technologies for business applicability since business units will generally lack the resources or the technological capability to perform these evaluations themselves. Moreover, central IT is best positioned to educate the end uses to make them good custmers of the central IT group. 　　In the banking industry, IT may be able to play an additional role in coordinating technology. Because banks and other financial firms are often managed with largely autonomous business units (for example, banks are often divided into product lines cash management, investmentor along customer segmentswholesale, mercial, retail) only the central IT function will have a perspective over the porfolio of systems projects and capabilities. One critical role in this respect is the provision and development of the shared IT infrastructure (. central processors, networks, software standards, etc.). Often these projects naturally span business units such that the only ral owner is the IT function。 see Berger, Kashyup and Scalise (1995) and Harker and Zenios (forthing) for a review of the banking efficiency literature. While there is substantial debate as to the role of these various factors, there is one unambiguous result: that most of the (in) efficiency of banks is not explained by the factors that have been considered in prior work. For example, Berger and Mester (1997) estimate that as much as 6590% of the xinefficiency remains unexplained after controlling for known drivers of performance. A similar story also appears in insurance where xefficiency varies substantially across firms when size, scope, product mix, distribution strategy and other strategic variables are considered. It has been argued that one must get inside the black box of the bank ot consider the role of organizational, strategic and technological factors that may be missed in studies that rely heavily on public financial data.　　 Information Technology and Business Value　　Early studies of the relationship between IT and productivity or other measures of performance were generally unable to determine the value of IT conclusively. Loveman (1994) and Strassmann (1990) ,using different data and analytical methods both found that the performance effects of puters were not statistically significant. Barus, Kriebel and Mukadopadhyay (1995), using the same data as Loveman, found evidence that IT improved some internal performance metrics such as inventory trunover, but could not tie these benefits to improvements in bottom line productivity. Although these studies had a number of disadvantages (small samples, noisy data ) which yielded imprecise measures of IT effects, this lack of evidence bined with equally equivocal macroeconomic ananlyses by Steven Roach (1987) implicitly formed the basis for the productivity paradox. As Robert Solow (1987) once remarked, you can see teh puter age everywhere except in the prod