This paper uses the relationships between three basic, fundamental and proven concepts
in manufacturing (resource commitment to improvement programs, flexibility to changes
in operations, and customer delivery performance) as the empirical context for reviewing
and comparing two casual modeling approaches (structural equation modeling and Bayesian
networks). Specifically, investments in total quality management (TQM), process analysis,
and employee participation programs are considered as resource commitments. The paper
begins with the central issue of the requirements for a model of associations to be
considered causal. This philosophical issue is addressed in reference to probabilistic
causation theory. Then, each method is reviewed in the context of a unified causal
modeling framework consistent with probabilistic causation theory and applied to a
common dataset. The comparisons include concept representation, distribution and functional
assumptions, sample size and model complexity considerations, measurement issues,
specification search, model adequacy, theory testing and inference capabilities. The
paper concludes with a summary of relative advantages and disadvantages of the methods
and highlights the findings relevant to the literature on TQM and on-time deliveries.
(C) 2003 Elsevier B.V. All rights reserved.
