【正文】 n modern building management system for improving and optimizing the energy and environmental performance of buildings. In addition, the application of wireless technologies with buildings or networking building systems is also a popular research area which has currently attracted attentions of many researchers and industry practitioners. Research in performance evaluation methodologiesApart from intelligent technologies research and development, there have been substantial amount of research devoting to evaluating intelligent building. Serafeimidis considered the evaluation process as a feedback mechanism aimed to facilitate learning, while considered the process of evaluation as ‘a(chǎn) series of activities incorporating understanding, measurement and assessment. It is either a conscious or tacit process which aims to establish the value of or the contribution made by a particular situation. . and can relate the determination of the worth of an object’.Building performance evaluation is a crucial procedure which offers feedback function on the performance of building materials and ponents for future improvement and reference (: cited in Ref.). Different authorities have tried to develop evaluation models to assess the performance of intelligent building . Early performance evaluation models were developed by Manning in 1965 and Markus et al. in and Schramm later (in 1997) improved their evaluation models and proposed an ‘integrative building performance evaluation framework’ to evaluate and review the stance in all six major phrases of building delivery and life cycle including planning, programming, design, construction, occupancy and recycling. Many similar studies have also been conducted attempting to measure the level of intelligence that a building exhibited and to set up criteria for selection of the best intelligent building .Preiser developed the ‘postoccupancy evaluation process model (POE)’ in order to determine the intelligence level of intelligent buildings. The POE process model is generally executed in three stages. First, to develop patible data collection instructions in the conceptual phase。 second, to apply and pilot testing of evaluation instruments in field studies on intelligent office building。 third, to carry out parative analysis of data collected and development of remendations and guidelines for the utilization of the datagathering instruments worldwide. Preiser and Schramm applied the POE process model to evaluate intelligent building in the crosscultural context and suggested that the POE model could ‘enhance building performance evaluation in intelligent buildings especially in a longterm, continuing basis’ because the evaluation system allows the ‘tracking of performance of new hightech systems and their effects on building occupants as well as the effectiveness of these systems in general’.Without a rating system, it is difficult to classify and justify the level of intelligence of intelligent buildings. Therefore, there have been many studies trying to develop rating systems for the intelligent building. One of the essential performance rating systems was the ‘building rating method’ developed by DEGW in 1995 based on the ‘building IQ rating method’ and the ‘building quality assessment’ (developed by Intelligent Buildings Europe Work). The method employs five categories of factors which are bined to produce overall assessments of the suitability of intelligence provided by the subject building. On the other hand, Arkin and Paciuk developed a ‘‘Magnitude of Systems’ Integration’’ Index (MSIR) to examine the level of systems’ integration of intelligent buildings according to the extent of integration among their systems, and between systems and the building’s structure. This assessment methodology can be used for evaluation and parison of single aspect of building’s intelligence and to create a unified index for evaluation of system’s integration in intelligent buildings. This model has been adapted by other researchers in the intelligent building performance evaluation such as Yang and Peng, 2001 . More recently, the Asian Institute of Intelligent Buildings constructed a quantitative assessment method, namely the intelligent building index (IBI). The individual assessment index for this methodology was originated from the nine ‘Quality Environment Modules’ (M1–M9), each index possesses a score which is a real number (within the range of 1–100) calculated by a conversion formula. A building can be ranked from A to E to indicate the overall intelligent performance. Research in investment evaluation analysisAnother stream of research has been focusing on evaluating economic and financial aspects of intelligent building, which is referred as the investment feasibility evaluation of intelligent building projects. Investment to intelligent building has increased dramatically in the Asia Pacific region in recent years. A number of authors suggested that the growing interest in investment has been credited to potential benefits that an intelligent building delivered to the investors. These benefits include ‘reducing operating and occupancy costs。 providing a flexible, convenient and fortable environment for occupants。 offering advanced technological facilities together with reduced maintenance costs。 and improving operational effectiveness, efficiency and marketability’. However, many investors have the mentality of ‘highrisk and lowreturn’ towards investment in intelligent building.There is a growing demand for tools to support intelligent building investment decisionmaking. For example, Choi pointed out that the financial viability of intelligent building is the major concern of the developers. Wong et al. argued that many investors would consider cost and benefit when they decide whether it is worthwhile to invest in a new technology. Also, Mawson remarked the necessity of justifying the intelligent building investment on the basis of cost