| Abstract: | Traditional capital budgeting theory (as an extension of financial economics) is characterized as Panglossian because of its suggestion that rational market outcomes produce the best of all possible worlds. During the last two decades, practice-oriented theorists have increasingly been moving from algorithmic capital budgeting techniques to a focus on capital investment strategy. Also, during the last twelve years, economics researchers at the Santa Fe Institute (SFI) have scrapped the dubious assumptions of neoclassical economics and have turned to complex adaptive systems theory for a more realistic portrayal of the economy. This paper explores various SFI studies and their implications for capital investment theory and capital investment strategy. Brian Arthur's theory of increasing returns undermines the notion that capital budgeting techniques can be counted on to generate economic efficiency. His theory further suggests that the high tech, knowledge-based sectors of the economy inherently produce outcomes that are too unpredictable for the meaningful application of traditional capital budgeting techniques. Studies by David Lane and his colleagues suggest that the identity of agents, the attributes of artifacts and the possibilities for action tend to be emergent phenomena that are generated by the interactions of agents. These considerations suggest a form of strategic action that focuses on process. Finally, it is argued that the artificial life and other SFI types of computer simulation models are potentially useful tools for the study of strategic capital investment decisions. |
