Trends in an international industrial engineering research journal: A textual information analysis perspective

Industrial engineering (IE) is a multi-disciplinary field, with its research borders broadening into a wide range of sub-disciplines. The Computers & Industrial Engineering (CaIE) journal is one of the prominent journals in the world to publish IE research and has done so since 1977. In the interest of evaluating research scope, it is worth determining how IE fields have been covered by this journal. What are the current topics in IE, and how are these positioned over time? This article attempts to investigate these issues in an objective way by using a text analytical technique to analyze the CaIE publication collection. Due to the growth in the quantity of accessible textual information, and the growing importance of this type of information to business people and industrial engineers alike, the basic methodological premise is provided for the topic modeling process. For the study presented in this paper, the Latent Dirichlet Allocation (LDA) topic modeling technique was applied to the CaIE corpus from 1977 to 2011 (Vol 60). The focus of this article is thus twofold: first, on interpreting the underlying topic trends in the CaIE’s publication history; and second, on introducing the concept of topic modeling whilst highlighting its value to the modern industrial engineer and researcher.

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