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An optimal multiple stopping approach to infrastructure investment decisions
Institution:1. Lenfest Center for Sustainable Energy, Department of Earth & Environmental Engineering, Columbia University, New York, NY 10027, United States;2. Department of Industrial Engineering & Operations Research, Columbia University, New York, NY 10027, United States;1. Dipartimento di Ingegneria Informatica, Automatica e Gestionale, Sapienza Università di Roma, Via Ariosto 25, 00185 Roma, Italy;2. Dipartimento di Scienze di Base e Applicate per l’Ingegneria, Sapienza Università di Roma, Via A. Scarpa 16, 00161 Roma, Italy;1. Department of Mathematical Sciences, The University of Liverpool, Liverpool, L69 7ZL, UK;2. Department of Mathematical Sciences, Xi''an Jiaotong-Liverpool University, 111 Ren''ai Road, Suzhou, 215123, People''s Republic of China;1. Department of Telecommunications and Systems Engineering, The Autonomous University of Barcelona, Carrer Emprius 2, Sabadell, Barcelona 08202, Spain;2. Department of Electrical and Computer Engineering, The University of Arizona, 1230 E. Speedway Boulevard, Tucson, AZ 85721, USA;3. Department of Surgery, College of Medicine, The University of Arizona, 1501 N. Campbell Avenue, Tucson, AZ 85724, USA;1. Department of Medicine, Albert Einstein College of Medicine/Montefiore Medical Center, Bronx, New York;2. Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, New York;3. Department of Medicine, Albert Einstein College of Medicine/Jacobi Medical Center, Bronx, New York
Abstract:The energy and material processing industries are traditionally characterized by very large-scale physical capital that is custom-built with long lead times and long lifetimes. However, recent technological advancement in low-cost automation has made possible the parallel operation of large numbers of small-scale and modular production units. Amenable to mass-production, these units can be more rapidly deployed but they are also likely to have a much quicker turnover. Such a paradigm shift motivates the analysis of the combined effect of lead time and lifetime on infrastructure investment decisions. In order to value the underlying real option, we introduce an optimal multiple stopping approach that accounts for operational flexibility, delay induced by lead time, and multiple (finite/infinite) future investment opportunities. We provide an analytical characterization of the firm?s value function and optimal stopping rule. This leads us to develop an iterative numerical scheme, and examine how the investment decisions depend on lead time and lifetime, as well as other parameters. Furthermore, our model can be used to analyze the critical investment cost that makes small-scale (short lead time, short lifetime) alternatives competitive with traditional large-scale infrastructure.
Keywords:Optimal multiple stopping  Real option  Infrastructure investments  Lead time  Operational flexibility
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