Northern Light's "meaning extraction" facility for automatically analyzing concepts within research literature is the enabling technology behind a newly published journal paper that assesses 30 years of research into information technology (IT) innovation adoption by enterprises.

The article, entitled "IT Innovation Adoption by Enterprises: Knowledge Discovery through Text Analytics", is being published in the January 2013 issue of Elsevier's Decision Support Systems journal; it is available online at http://www.sciencedirect.com/science/article/pii/S0167923612002849. It is the first scholarly investigation of enterprise IT innovation to use automated full-text mining to extract key phrases and information from relevant literature, identify central themes, and apply concept linking.

Northern Light CEO C. David Seuss is one of three co-authors of the paper. The others are Rahul C. Basole, an associate professor at the School of Interactive Computing & Tennenbaum Institute at Georgia Institute of Technology in Atlanta; and William B. Rouse of the School of Systems & Enterprises at Stevens Institute of Technology in Hoboken, New Jersey.

The paper offers an assessment of the current state of enterprise IT adoption research by providing a comprehensive classification and analysis of the scholarly literature.  Some of the findings contained in the article include: "Emerging IT innovations have the potential to radically transform enterprises.  They have been shown to lead to new means of data and information access, transmission and exchange, as well as new organizational structures. Emerging IT innovations may also lead to new administrative IT requirements and responsibilities, such as security policies and enterprise device management."

In contrast to most previous review studies, which limited their analysis to five to 10-year time spans, the new article provides a comprehensive picture of the scholarly development and trajectory of research over three decades, and therefore identifies important longitudinal trends in enterprise-level IT innovation adoption topics, methods, drivers, inhibitors, and contexts. The use of text mining, in the form of Northern Light's automated meaning extraction technology, enabled researchers to identify topical relationships and discover research trends in a large set of documents across multiple scholarly domains.

"Traditional literature analyses are often time and resource intensive," Seuss said. "Text analytics overcomes these challenges by applying automated means to extract and discover knowledge in unstructured data sources. From an analysis perspective, the ability to detect and measure relationships between text strings can be very useful if used to extract meaning rather than to expand search terms."

Today, meaning extraction is beginning to be applied by companies to search electronic document repositories and various online resources to dramatically improve and accelerate a researcher's ability to gain insight into a topic and answer specific research questions, according to Seuss. The technology is incorporated into Northern Light's SinglePoint™ strategic research portals. SinglePoint portals enable integrated search and automated analysis of a company's primary and licensed secondary market and technical research, as well as other industry news and information that is valuable for competitive intelligence, strategic planning, product development, and other business functions.

PR Newswire - January 9, 2013