Simulation is an important method, but its link to theory development remains unclear and even controversial. Our purpose is to clarify when and how to use simulation methods in theory development. First, we develop a roadmap for conducting theory development using simulation methods. It ranges from selecting the research question and simple theory to conducting verification and validation. The primary value of simulation occurs in creative and systematic experimentation to produce novel

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... Second, we position simulation methods within the broad context of theory development. Simulation sits in the "sweet spot" between theory creating using methods such as multiple case inductive studies and formal modeling, and theory testing using methods such as multivariate statistical testing of hypotheses. We note the strengths of theory building using simulation including internal validity, experimentation to create new theory, and facility in coping with longitudinal, non-linear, and process phenomena, especially when empirical data are challenging to obtain. We also note simulation's weaknesses such as external validity. We conclude with guidelines for evaluation that focus on the importance of theoretical contribution, strength of method, and the insights of the emergent theory. ) and strategies (Rivkin, 2001) . The results of research using simulation methods can also be dynamically indeterminate and overly complex (Fichman, 1999) . From these perspectives, the value of simulation methods for theoretical development is tenuous. The controversy surrounding the value of simulation methods for theory development partially arises, in our view, from a lack of clarity about the method and its related link to theory development. There appears to be limited understanding within the broad research community about (1) when simulation is a useful methodological choice for theory development, (2) how to select among the various simulation approaches (e.g., system dynamics vs. genetic algorithms), (3) the appropriate steps for performing simulation research, and (4) the relevant criteria for evaluating simulation research. Most significant, there seems to be limited recognition within the research community of how simulation methods fit into the broader scheme of relating methodological choices to theoretical development. Our purpose is to address these issues by clarifying when and how to use simulation methods in theory development. Although scholars writing about theory development (e.g., Dubin, 1976; Pfeffer, 1982; Priem & Butler, 2001; Sutton & Staw, 1995; Whetten, 1989) may have different emphases, most agree that theory has four elements: constructs, propositions that link those constructs together, logical arguments that explain the underlying theoretical rationale for the propositions, and assumptions that define the scope or boundary conditions of the theory. i Consistent with these views, we define theory as consisting of constructs linked together by propositions that have an underlying, coherent logic and related assumptions. Broadly, we attempt to make two contributions. First, we offer a roadmap for how to use simulation methods to develop theory. This roadmap synthesizes prior work on the design of simulation research (e.g., Sterman, 2000) and extends that work into specific areas such as