Abstract
As more and more manufacturing companies accumulate profits from service provision, the ability to monitor the adoption of the industrial services of other companies grows more important. The purpose of this paper is to propose a data-driven methodology for extraction of the industrial service portfolio from a company’s annual report. In this approach, form 10-K, a special format of annual report regulated by the Security Exchange Commission in United States is utilized as the data source. Because this document type contains rich information on a company’s operating segments, industrial service information is easily retrieved. Given the sheer volume of such documents, however, manual inspection is impractical. In order to resolve this issue, a text-mining algorithm is applied to automatically examine word-usage patterns and to identify the service portfolio. Then, the service portfolio’s relative position in the market is visualized on a positioning map. Due to the multi-dimensionality of the data, self-organizing map (SOM) is used as an alternative visualization scheme. SOM enables easy identification of the major service clusters as well as niche areas in the market; these, in turn, provide valuable information pertinent to service development planning. Also, and not least, policy makers can utilize our methodology to detect the servitization trends of various industries.
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Acknowledgments
This work was supported by the “Core Technology Development Program for Knowledge-Based Service” funded by the Korean Government (MOTIE) (Project No. 10048090, Title: Manufacturing Servitization Support Framework). The authors deeply appreciate the administrative support during the project period from Institute for Industrial Systems Innovation of Seoul National University.
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An erratum to this article is available at http://dx.doi.org/10.1007/s10696-016-9243-9.
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Lee, J., Hong, Y.S. Extraction and visualization of industrial service portfolios by text mining of 10-K annual reports. Flex Serv Manuf J 28, 551–574 (2016). https://doi.org/10.1007/s10696-015-9235-1
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DOI: https://doi.org/10.1007/s10696-015-9235-1