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In previous reports, we have identified two potentially important issues, solutions to which would increase the attractiveness of DOE-developed technologies in commercial buildings energy systems. One issue concerns the fact that in addition to saving energy, many new technologies offer non-energy benefits that contribute to building productivity (firm profitability). The second issue is that new technologies are typically unproven in the eyes of decision makers and must bear risk premiums that offset cost advantages resulting from laboratory calculations. Even though a compelling case can be made for the importance of these issues, for building decision makers to incorporate them in business decisions and for DOE to use them in R&amp;D program planning there must be robust empirical evidence of their existence and size. This paper investigates how such measurements could be made and offers recommendations as to preferred options. There is currently little systematic information on either of these concepts in the literature. Of the two there is somewhat more information on non-energy benefits, but little as regards office buildings. Office building productivity impacts can be observed casually, but must be estimated statistically, because buildings have many interacting attributes and observations based on direct behavior can easily confuse the process of attribution. For example, absenteeism can be easily observed. However, absenteeism may be down because a more healthy space conditioning system was put into place, because the weather was milder, or because firm policy regarding sick days had changed. There is also a general dearth of appropriate information for purposes of estimation. To overcome these difficulties, we propose developing a new data base and applying the technique of hedonic price analysis. This technique has been used extensively in the analysis of residential dwellings. There is also a literature on its application to commercial and industrial buildings. Commercially available data bases exist that, if supplemented with engineering survey for equipment and materials use, could be analyzed statistically with a hedonic price model for the valuation of both the energy-saving and productivity effects of building technologies. Uncertainties about technology performance can cause investors to delay deploying new technologies. This behavior is explained by the ''investment under uncertainty'' literature. This literature suggests that under conditions of irrecoverable (''sunk'') costs, uncertain outcomes, and the ability to defer deployment, decision makers focus on potential losses and demand risk premiums and a few support the notion of focusing on losses, the so-called ''bad news principle.'' We describe a series of approaches to isolating buyer perceptions of uncertainty and means for reducing uncertainty

Measurement Issues for Energy Efficient Commercial Buildings: Productivity and Performance Uncertainties