SAO-Based Semantic Mining of Patents for Semi-Automatic Construction of a Customer Job Map

Joohyung Lim, Sungchul Choi, Chiehyeon Lim and Kwangsoo Kim
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Joohyung Lim: Department of Industrial and Management Engineering, Pohang University of Science and Technology, Pohang, Gyeongsangbuk-do 37673, Korea
Sungchul Choi: Department of Industrial and Management Engineering, Gachon University, Seongnam, Gyeonggi-do 13120, Korea
Chiehyeon Lim: School of Management Engineering, Ulsan National Institute of Science and Technology, Ulsan 44919, Korea
Kwangsoo Kim: Department of Industrial and Management Engineering, Pohang University of Science and Technology, Pohang, Gyeongsangbuk-do 37673, Korea

Sustainability, 2017, vol. 9, issue 8, 1-17

Abstract: The Outcome-Driven Innovation (ODI) method based on the ‘Jobs-to-be-done’ concept is very useful in the identification of unmet customer needs and has been adopted widely in the industry. The Job Map, a tool of the ODI method, is used to understand customers by defining their behavioral process. Complications must be overcome before the Job Map can be applied to the specific problem in question, such as a time-consuming process, dealing with a large amount of data, and experts’ biased work. To solve these problems, this study develops a patent mining-based method based on the subject-action-object (SAO) structure to support the creation of a Job Map by semi-automatizing data collection and analysis. This effort at better utilizing computers in customer analysis for product design will contribute to expanding computerized methods for solving design and engineering problems in practice.

Keywords: customer needs; outcome-driven innovation (ODI); job map; jobs-to-be-done; patent text mining; subject-action-object (SAO) (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (8)

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