Economic appraisal and risk analysis of construction automation

This thesis sets forth the results of research into the economic appraisal and risk analysis of construction automation investment. The research development and use of automated plant and machinery for the construction industry has become a reality. The valuation of construction automation is inhibited by inadequate appraisal techniques. Furthermore, the dominant role of the plant hire industry has been ignored within existing valuation methodologies. An international review of existing prototype and manufactured technologies is presented. Unsuccessful technologies are highlighted, as are systems that provide valuable operational advantages to the international construction industries. A selective study of Japanese main contractors, using focus group interviews, highlighted existing capabilities, and identified key directions for future research. The focus groups provide a qualitative analysis of the limitations of historical research and ongoing construction automation operations. The inadequacies of valuation procedures are confirmed through a critical review of the existing valuation methodologies. Discontinuities within the existing literature influence the development of a generic financial risk analysis model and the application of real option pricing theory to the strategic valuation of construction automation. Specifically, the dominant role of the plant hire industry is incorporated through the valuation of automated technology from the perspective of a plant hire company. A probabilistic financial risk analysis model is developed to perform a hypothetical financial risk analysis. Furthermore, the application of real option-pricing theory to the valuation of construction automation investment is presented. Timing, learning, abandonment, strategic growth and switching option scenarios are described within the context of construction automation valuation and worked examples are presented. Finally, the limitations and validation of such valuation models are outlined. The thesis provides insight into the potential strategic value of construction automation.