期刊
SYSTEMS ENGINEERING
卷 18, 期 3, 页码 253-268出版社
WILEY
DOI: 10.1002/sys.21301
关键词
design flexibility; real options; project valuation; economies of scale; learning; LNG
资金
- National University of Singapore (NUS) Faculty Research Committee via MoE AcRF Tier 1 [WBS R-266-000-061-133]
- Singapore Agency for Science, Technology and Research (A*STAR)
This paper presents an innovative flexibility analysis as a practical, effective procedure to improve the expected value of large-scale, capital-intensive projects when there is market uncertainty. Its novelty lies in its approach and scope. Its approach develops understanding of the drivers of the value of flexibility, so as to build acceptance among decision-makers. Its scope explicitly considers the combined effects of uncertainty, economies of scale, learning, and geographic distribution. It demonstrates how these factors combine to impact the benefits of flexibility in the early stages of design and project evaluation in the context of uncertainty. It makes this point through a specific example: the long-term deployment of liquefied natural gas (LNG) technology to supply the transportation market. It contrasts the base case fixed design (a big centralized production facility) with flexible modular designs that phase capacity additions over time and space. The proposed flexibility method compares design alternatives based on several indicators of economic lifecycle performance (Net Present Value (NPV), Initial Capex, etc.). Results indicate that flexible modular deployment strategies can significantly improve the economic performance of large, expensive projects. As sensitivity analyses show, the improvements can be significant over a wide range of analytical assumptions. An important insight is that higher learning rates increase the benefits of flexibility, counteracting the effects of economies of scale. Overall, the study shows that flexibility in engineering design of major production facilities such as LNG plants has multiple, supporting advantages due to uncertainty, learning, and location.
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