Browse by author
Lookup NU author(s): Professor Stewart RobinsonORCiD
Full text for this publication is not currently held within this repository. Alternative links are provided below where available.
© 2018 Elsevier B.V.Can language usage help determine which model approach is best suited to provide decision makers with desired insights? This research addresses that question through an investigation of Linguistic Inquiry and Word Count (LIWC), which calculates the presence of >80 language dimensions in text samples, and permits construction of custom dictionaries. This article demonstrates use of LIWC to ensure better problem/model fit within the context of selecting a decision support tool. We selected two simulation tools as research instruments to investigate a broader question on the usefulness of LIWC to guide choice of DSS tool. The tools selected were System Dynamics (SD) and Discrete Event Simulation (DES). First, we tested LIWC to analyze practitioners’ language use when developing models. LIWC pointed out significant linguistic differences consistent with prior theoretical work, based on model development approach in a number of dimensions. These differences provided a basis for developing a custom dictionary for use on the second part of our study. The second part of the study focused on language used by decision makers in problem statements and used the linguistic clues identified in the first part of the study to ensure problem/model fit. Results indicated problem statements contained linguistic clues related to the type of information desired by problem solvers. The article concludes with a discussion about how LIWC and similar tools can help determine which DSS tools are suited to particular applications.
Author(s): McHaney R, Tako A, Robinson S
Publication type: Article
Publication status: Published
Journal: Decision Support Systems
Year: 2018
Volume: 111
Pages: 1-12
Print publication date: 01/07/2018
Online publication date: 19/04/2018
Acceptance date: 17/04/2018
ISSN (print): 0167-9236
ISSN (electronic): 1873-5797
Publisher: Elsevier B.V.
URL: https://doi.org/10.1016/j.dss.2018.04.002
DOI: 10.1016/j.dss.2018.04.002
Altmetrics provided by Altmetric