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Who Wins in a Dynamic World: Theory of Constraints Vs. Activity-Based Costing?
North American Assoc. for Computational Social and Organizational Science (NAACSOS) Conference (2007)
  • Robin Cooper, Emory University
  • David A. Bray, National Defense University
  • Michael Parzen, Emory University
Abstract

Two system-based views exist regarding managerial value chain analysis: Theory of Constraints (TOC) and Activity-Based Costing (ABC). There has been considerable debate whether TOC or ABC is the more optimal approach for strategic planning. This study seeks to compare TOC and ABC, while keeping constant the level of environmental turbulence each of the approaches encounter. With regard to organizational systems, literature regarding complex adaptive systems supports the idea that bottom-up approaches are more resilient to volatility. Consequently, this study hypothesizes that the bottom-up ABC approach will prove more agile and less limiting than the top-down TOC approach. This study then performs two computational experiments. The first experiment reveals that the ABC approach generated more PROFIT than the TOC approach, while the TOC produced a larger amount of REVENUE, for all instances of the simulation. The second experiment reveals that a hybrid TOC+ABC approach is the most optimal in the midst of environmental turbulence out of four possibilities. This hybrid TOC+ABC selects a first cut of orders that will generate the highest REVENUES per the TOC approach, and then selects a second cut of orders that will have the lowest COSTS and thus the highest PROFIT per the ABC approach. These results challenge the established literature espousing the TOC approach alone.

Keywords
  • Theory of Constraints (TOC),
  • Activity-Based Costing (ABC),
  • value chain analysis,
  • strategic planning,
  • bottom-up approaches,
  • environmental turbulence
Publication Date
June, 2007
Citation Information
Robin Cooper, David A. Bray and Michael Parzen. "Who Wins in a Dynamic World: Theory of Constraints Vs. Activity-Based Costing?" North American Assoc. for Computational Social and Organizational Science (NAACSOS) Conference (2007)
Available at: http://works.bepress.com/dbray/1/