Computational Design Synthesis of Aircraft Configurations with Shape Grammars

  • Oberhauser M
  • Sartorius S
  • Gmeiner T
  • et al.
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Abstract

In the published proceedings of the first Journal of Accounting Research Con- ference, Vatter [1966] lamented that “Gathering direct and original facts is a tedious and difficult task, and it is not surprising that such work is avoided.” For the fiftieth JAR Conference, we introduce a framework to help researchers understand the complementary value of seven empirical methods that gather data in different ways: prestructured archives, unstructured (“hand-collected”) archives, field studies, field experiments, surveys, laboratory studies, and laboratory experiments. The framework spells out five goals of an empirical literature and defines the seven methods according to researchers’ choices with respect to five data gathering tasks. We use the framework and examples of successful research studies in the financial reporting literature to clarify how data gathering choices affect a study’s ability to achieve its goals, and conclude by showing how the complementary nature of different methods allows researchers to build a literature more effectively than they could with less diverse approaches to gathering data.

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APA

Oberhauser, M., Sartorius, S., Gmeiner, T., & Shea, K. (2015). Computational Design Synthesis of Aircraft Configurations with Shape Grammars. In Design Computing and Cognition ’14 (pp. 21–39). Springer International Publishing. https://doi.org/10.1007/978-3-319-14956-1_2

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