【正文】 ve very high investments but are poor performers, while otheres invest less but appear to be much more successful. Brynjolfsson and Hitt found that as much as half the returns to IT investment are due to firm specific factors.　　One potentially important driver of differences in IT value, and of firm performance more broadly, is likely to be the decision and management peocessed for IT investments. Horror stories of bad IT investment decisions abound. Consider the example of the new strategic banking system(SBS) at Banc One(American Banker 1997). Banc One Corp. and Electronic Data Systems Corp. agreed last year to end their joint development of this retail banking system after spending an estimated $175 million on it. As stated in the American Banker article, SBSwas just so overwhelming and so plete that by the time they were getting to market, it was going to take too long to install the whole thing, said Alan Riegler, principal in Ernst amp。 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 productivity statistics.　　 More recent work has found that IT investment is a substantial contributor to firm productivity, productivity growth and stock market valuation in a sample that contains a wide range of industries. Brynjolfsson and Hitt (1994,1996) and Lichtenberg (1995) found that IT investment had a positive and statistically significant contribution to firm output . Brynjolfsson and Yang (1997) found that the market valuation of IT capital was several times that of ordinary capital. Brynjolfsson and Hitt also found a strong relationship between IT and productivity growth and taht this relationship grows stronger as longer time periods are considered. Collectively ,these studies suggest that there is no productivity paradox, at least when the analysis is performed across industries using firmlevel data. The differences between these results and earlier studies is probably due to the use of data taht was recent , more prehensice ,and more disaggregated (firm level rather than industry or economy level). 　　Most previous sutdies have considered the effects of technology across firms in multiple industries, although a few studies have considered the role of technology in specifically in the banking industry. Steiner and Teixiera surveyed the banking industry and argued that while large investments in technology clearly had value,little of this value was being captured by the banks themselves。 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 p