Equipment Replacement Under Continuous and Discontinuous Technological Change

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This grant provides funding for research into the modeling and solution of equipment replacement problems that incorporate both continuous and discontinuous technological change. Continuous technological change refers to the gradual improvement in assets available over time for replacement. These generally coincide with the manufacturer periodically releasing new models, which are more efficient than previous models. Discontinuous technological change refers to breakthroughs in technology, often accompanied by jumps in productivity when compared to previous models. We assume breakthroughs define a new vintage of asset that gradually improves in subsequent model releases of the same vintage. In either case, the economic impact of the technology may not be known until it arrives. Stochastic dynamic programming is proposed to solve this problem under various scenarios of technological, capital budgeting constraints, and multiple suppliers. Due to the large state space of the system, approximation techniques will be used to allow for the solution of longer horizon problems, ensuring (near) optimal time zero decisions. The expected benefits of this work lie in the ability to determine optimal or near optimal policies for consumers of technological assets, such as hospitals. To verify these insights, Lehigh Valley Hospital has offered data on over 24,000 pieces of medical equipment. This information will allow for the application of the developed models.Furthermore, extensions of this work will more closely examine how to influence consumers' choices concerning technological change. For example, manufacturers may offer maintenance contracts or pecialized warranties in order to entice purchases while sharing the risk of using newer technologies. Furthermore, governments may offer incentives for manufacturers to adopt newer technologies with greater investment.These policies can be examined by analyzing the optimal replacement policies under differing conditions. The benefits of these analyses will be in designing methods (policies and contracts) that foster capital investment and technological innovation.